We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 11, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 11, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 11, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Overview Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We're building a more open world. Join us. Expedia's InsurTech Product team creates peace of mind so travellers and partners can book, host, and travel with confidence. As a high performing product organization, the team plays a critical role in shaping how millions of customers experience protection across Expedia brands worldwide. The team owns products end-to-end, from early concept and product design through supplier integration, regulatory approval, and global launch. Working closely with actuaries, machine learning scientists, engineers, designers, and commercial partners, InsurTech delivers complex, regulated products across multiple markets while leveraging data and AI to personalize experiences at scale. Responsibilities In this role, you will: Launch new insurance products and expand existing offerings into new geographies, driving execution in a highly complex, global environment. Partner with actuaries, ML scientists, and data teams to identify unmet customer needs and define insurance product structures, including benefits, limits, eligibility, and pricing. Own insurance products end-to-end from concept through live production, ensuring alignment with both customer and commercial outcomes. Lead cross-functional collaboration with Legal, Engineering, Design, and Data teams to ensure seamless product delivery. Enable AI-driven personalization and targeting, leveraging data and AI insights to inform product decisions. Lead integration with insurance and non-insurance suppliers, balancing customer value, technical and experience considerations. Qualifications Minimum Qualifications: Bachelor's degree in a relevant field or equivalent related professional experience. 5+ years of relevant professional experience in product management or related technical domains. Ability to clearly identify and articulate customer needs and define customer-centric product strategy to address those. Proven experience owning product lifecycle from ideation through launch and iterative improvement within a multi-team or multi-service environment. Experience working on insurance or other regulated financial products, with a strong understanding of insurance concepts such as risk, coverage, pricing, and eligibility. Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products. Preferred Qualifications Track record of delivering regulated insurance products that operate at scale, with a focus on customer adoption and measurable business impact. Experience leading architecture and design discussions, including integrating AI/ML-enabled features for enhanced insurance product functionality. Advanced proficiency in leveraging analytics and AI insights to inform product direction and measure success. Deep understanding of emerging AI/ML trends and their practical application in insurance product management, with the ability to safely integrate new technologies. Accommodations Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Group's family of brands includes: Brand Expedia Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: -50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you're confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain The official website to find and apply for job openings at Expedia Group is Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Mar 10, 2026
Full time
Overview Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We're building a more open world. Join us. Expedia's InsurTech Product team creates peace of mind so travellers and partners can book, host, and travel with confidence. As a high performing product organization, the team plays a critical role in shaping how millions of customers experience protection across Expedia brands worldwide. The team owns products end-to-end, from early concept and product design through supplier integration, regulatory approval, and global launch. Working closely with actuaries, machine learning scientists, engineers, designers, and commercial partners, InsurTech delivers complex, regulated products across multiple markets while leveraging data and AI to personalize experiences at scale. Responsibilities In this role, you will: Launch new insurance products and expand existing offerings into new geographies, driving execution in a highly complex, global environment. Partner with actuaries, ML scientists, and data teams to identify unmet customer needs and define insurance product structures, including benefits, limits, eligibility, and pricing. Own insurance products end-to-end from concept through live production, ensuring alignment with both customer and commercial outcomes. Lead cross-functional collaboration with Legal, Engineering, Design, and Data teams to ensure seamless product delivery. Enable AI-driven personalization and targeting, leveraging data and AI insights to inform product decisions. Lead integration with insurance and non-insurance suppliers, balancing customer value, technical and experience considerations. Qualifications Minimum Qualifications: Bachelor's degree in a relevant field or equivalent related professional experience. 5+ years of relevant professional experience in product management or related technical domains. Ability to clearly identify and articulate customer needs and define customer-centric product strategy to address those. Proven experience owning product lifecycle from ideation through launch and iterative improvement within a multi-team or multi-service environment. Experience working on insurance or other regulated financial products, with a strong understanding of insurance concepts such as risk, coverage, pricing, and eligibility. Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products. Preferred Qualifications Track record of delivering regulated insurance products that operate at scale, with a focus on customer adoption and measurable business impact. Experience leading architecture and design discussions, including integrating AI/ML-enabled features for enhanced insurance product functionality. Advanced proficiency in leveraging analytics and AI insights to inform product direction and measure success. Deep understanding of emerging AI/ML trends and their practical application in insurance product management, with the ability to safely integrate new technologies. Accommodations Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Group's family of brands includes: Brand Expedia Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: -50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you're confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain The official website to find and apply for job openings at Expedia Group is Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Associate Scientist page is loaded Associate Scientistlocations: UK - Oxfordtime type: Full timeposted on: Posted Yesterdayjob requisition id: RGENEWIZ UK Ltd At Azenta, new ideas, new technologies and new ways of thinking are driving our future. Our customer focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships. All we accomplish is grounded in our core values of Customer Focus, Achievement, Accountability, Teamwork, Employee Value and Integrity Job TitleAssociate Scientist Job Description Company Overview Our NGS Lab team is looking for a new talent, starting at the earliest possible time as Associate Scientist . Location: Oxford Permanent, full-time employment How You Will Add Value The Associate Scientist position in our Next Generation Sequencing department is a great entry-level role with room for growth and advancement. If you have the desire to work in a casual yet results-driven environment that embraces innovation- then you're just what we're looking for! What You Will Do Prepare amplified template libraries for high-throughput sequencing Carry out DNA sequencing on next-generation DNA analyzers Perform routine maintenance of DNA analyzers and related equipment Check inventory and replenish consumable sequencing supplies Communicate with customers by phone and e-mail in a friendly and professional manner Follow SOPs and guidance of supervisors Be an effective team-player committed to company goals What You Will Bring Bachelor's Degree in Biological Sciences required, advanced degree preferred Knowledge of standard laboratory processes Follow and help to develop Standard Operating Protocol (SOP) Strong communications/interpersonal skills, both verbal and written, are essential. Sequencing experience (NGS) preferred. Our Offer Become part of a company that makes a positive contribution to launching groundbreaking scientific developments and therapies. Contribute to innovative cell therapies and be a part of revolutionary cancer therapies. Take advantage of the operational opportunities in a growing, modern, and innovative company within the health care/life science industry. Experience an intensive exchange of experiences and close cooperation in a worldwide network with our customers, friends, and partners. After your initial training, you will receive regular training and further education opportunities that are tailored to your needs. A workplace that promotes your maximum. Positive corporate culture and practiced teamwork across all locations. Our other benefits include: Private Medical Insurance. Employee Assistance Programme. Company Pension. Life Insurance. Electric vehicle leasing. Cycle to Work. Denplan. Azenta Employee Stock Purchase Plan (ESPP). Company bonus scheme LinkedIn Learning cooperation. At GENEWIZ, from Azenta Life Sciences, new ideas, new technologies and new ways of thinking are driving our future. Our customer-focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships.GENEWIZ is a global leader in multiomics and synthetic solution services with headquarters in South Plainfield, NJ and offices and operations worldwide. We empower our customer's research by providing high-quality, precision-based solutions from discovery through clinical development, enabling scientists to make breakthroughs faster and more efficiently. Key services include Next Generation and Sanger sequencing, gene synthesis, gene-to-discovery solutions including antibody production, viral packaging and mRNA synthesis. Together with our customers, we can be the partner of choice for life science communities worldwide, driving advancements that foster innovation across the globe. If any applicant is unable to complete an application or respond to a job opening because of a disability, please email at for assistance. Azenta is an Equal Opportunity Employer. This company considers candidates regardless of race, color, age, religion, gender, sexual orientation, gender identity, national origin, disability or veteran status.
Mar 10, 2026
Full time
Associate Scientist page is loaded Associate Scientistlocations: UK - Oxfordtime type: Full timeposted on: Posted Yesterdayjob requisition id: RGENEWIZ UK Ltd At Azenta, new ideas, new technologies and new ways of thinking are driving our future. Our customer focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships. All we accomplish is grounded in our core values of Customer Focus, Achievement, Accountability, Teamwork, Employee Value and Integrity Job TitleAssociate Scientist Job Description Company Overview Our NGS Lab team is looking for a new talent, starting at the earliest possible time as Associate Scientist . Location: Oxford Permanent, full-time employment How You Will Add Value The Associate Scientist position in our Next Generation Sequencing department is a great entry-level role with room for growth and advancement. If you have the desire to work in a casual yet results-driven environment that embraces innovation- then you're just what we're looking for! What You Will Do Prepare amplified template libraries for high-throughput sequencing Carry out DNA sequencing on next-generation DNA analyzers Perform routine maintenance of DNA analyzers and related equipment Check inventory and replenish consumable sequencing supplies Communicate with customers by phone and e-mail in a friendly and professional manner Follow SOPs and guidance of supervisors Be an effective team-player committed to company goals What You Will Bring Bachelor's Degree in Biological Sciences required, advanced degree preferred Knowledge of standard laboratory processes Follow and help to develop Standard Operating Protocol (SOP) Strong communications/interpersonal skills, both verbal and written, are essential. Sequencing experience (NGS) preferred. Our Offer Become part of a company that makes a positive contribution to launching groundbreaking scientific developments and therapies. Contribute to innovative cell therapies and be a part of revolutionary cancer therapies. Take advantage of the operational opportunities in a growing, modern, and innovative company within the health care/life science industry. Experience an intensive exchange of experiences and close cooperation in a worldwide network with our customers, friends, and partners. After your initial training, you will receive regular training and further education opportunities that are tailored to your needs. A workplace that promotes your maximum. Positive corporate culture and practiced teamwork across all locations. Our other benefits include: Private Medical Insurance. Employee Assistance Programme. Company Pension. Life Insurance. Electric vehicle leasing. Cycle to Work. Denplan. Azenta Employee Stock Purchase Plan (ESPP). Company bonus scheme LinkedIn Learning cooperation. At GENEWIZ, from Azenta Life Sciences, new ideas, new technologies and new ways of thinking are driving our future. Our customer-focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships.GENEWIZ is a global leader in multiomics and synthetic solution services with headquarters in South Plainfield, NJ and offices and operations worldwide. We empower our customer's research by providing high-quality, precision-based solutions from discovery through clinical development, enabling scientists to make breakthroughs faster and more efficiently. Key services include Next Generation and Sanger sequencing, gene synthesis, gene-to-discovery solutions including antibody production, viral packaging and mRNA synthesis. Together with our customers, we can be the partner of choice for life science communities worldwide, driving advancements that foster innovation across the globe. If any applicant is unable to complete an application or respond to a job opening because of a disability, please email at for assistance. Azenta is an Equal Opportunity Employer. This company considers candidates regardless of race, color, age, religion, gender, sexual orientation, gender identity, national origin, disability or veteran status.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Overview Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen. Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Team 90 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first-principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Diego Protas - Director of Engineering Diego, an expert in distributed systems and hardware architecture, merging physical computing with enterprise-scale infrastructure. Previously directing teams of 170+ engineers at Mercado Libre and orchestrating large-scale ML-based inference at Meta. At Relay, Diego's infectious enthusiasm and hands-on leadership are redefining the boundaries of speed and reliability. Tech Stack Highlights Python, Rust and TypeScript - we keep things simple but use the right tool for the job Cross-platform Flutter apps with a deep focus on user experience Cloud-native on GCP with extensive use of BigQuery and Cloud Run Extensive use of ML modelling and LLM inference - no gimmicks here, this is our daily routine Emerging tech integrations, including robotics and IoT-powered operations The Opportunity As a Software Engineer at Relay, you'll: Own challenging, impactful problems end-to-end, from routing algorithms to real-time optimisation services and intuitive operational tools. Collaborate closely with top engineers, data scientists, and product leaders in a highly autonomous and impact-driven environment. Regularly ship production-quality code weekly-and often daily-seeing your work directly impact Relay's growth. Create incredible product experiences powering the fastest-growing e-commerce platforms, including Vinted, TikTok, and Temu, impacting millions of users worldwide. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min API Integration Interview - 1 hour Technical Interview - 2 hours Operating Principles & Impact - 1 hour Decision and offer within 48 hours; our process mirrors our pace of work, typically completed in a week. Compensation, Benefits & Workplace Generous equity, richer than 99% of European startups, with annual top-ups to share Relay's success. Private health & dental coverage, so comprehensive you'd need to be a partner at a Magic Circle law firm to match it. 25 days of holidays Enhanced parental leave Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote. Hardware of your choice Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more). Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Mar 10, 2026
Full time
Overview Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen. Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Team 90 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first-principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Diego Protas - Director of Engineering Diego, an expert in distributed systems and hardware architecture, merging physical computing with enterprise-scale infrastructure. Previously directing teams of 170+ engineers at Mercado Libre and orchestrating large-scale ML-based inference at Meta. At Relay, Diego's infectious enthusiasm and hands-on leadership are redefining the boundaries of speed and reliability. Tech Stack Highlights Python, Rust and TypeScript - we keep things simple but use the right tool for the job Cross-platform Flutter apps with a deep focus on user experience Cloud-native on GCP with extensive use of BigQuery and Cloud Run Extensive use of ML modelling and LLM inference - no gimmicks here, this is our daily routine Emerging tech integrations, including robotics and IoT-powered operations The Opportunity As a Software Engineer at Relay, you'll: Own challenging, impactful problems end-to-end, from routing algorithms to real-time optimisation services and intuitive operational tools. Collaborate closely with top engineers, data scientists, and product leaders in a highly autonomous and impact-driven environment. Regularly ship production-quality code weekly-and often daily-seeing your work directly impact Relay's growth. Create incredible product experiences powering the fastest-growing e-commerce platforms, including Vinted, TikTok, and Temu, impacting millions of users worldwide. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min API Integration Interview - 1 hour Technical Interview - 2 hours Operating Principles & Impact - 1 hour Decision and offer within 48 hours; our process mirrors our pace of work, typically completed in a week. Compensation, Benefits & Workplace Generous equity, richer than 99% of European startups, with annual top-ups to share Relay's success. Private health & dental coverage, so comprehensive you'd need to be a partner at a Magic Circle law firm to match it. 25 days of holidays Enhanced parental leave Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote. Hardware of your choice Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more). Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Agentic AI Risk Modelling and Mitigations London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is Sunday 8 March 2026, end of day, anywhere on Earth. Team description As AI systems grow more capable and autonomous, understanding how humans could lose the ability to oversee, correct, or shut down these systems becomes critical - as does identifying what we can do to prevent it. Risk models for AI agents (for example, loss of control risk models) remain far less developed than those in comparable domains like cybersecurity and chem bio, and practical mitigations remain underexplored (especially beyond traditional alignment and control work). AISI is building a new team to close this gap. The new Agentic AI Risk Modelling and Mitigations team will develop rigorous models of how agentic AI could cause harm, identifying practical mitigations with a focus on measures the UK government are well placed to implement. We will draw on expertise only available within government - especially the national security community - to develop risk models and mitigations far more developed than those in academia or industry. The hiring manager for this role is Benjamin Hilton; the team is advised by Geoffrey Irving. You'll collaborate closely with researchers across AISI's red teams, evaluation teams, and alignment team, as well as with government stakeholders. Your work will draw on empirical evidence from AISI's evaluations, along with the broader cybersecurity and ML literature to develop detailed and precise threat models and mitigations. You'll need to reason carefully about complex and uncertain scenarios and communicate findings clearly to both technical researchers and policy decision makers. Some projects may also involve hands on ML or cybersecurity work, in collaboration with government partners, to develop mitigations. We are open to hires at junior, senior, staff, and principal research scientist levels. We may also make an offer to particularly promising candidates with management experience to lead the workstream in a management role. Representative projects you might work on Developing detailed models of specific loss of control scenarios - such as deceptive alignment during internal deployment, or a long horizon agentic cyberattack - specifying their causal structure, key assumptions, and plausibility given current and projected AI capabilities and propensities. Translating risk models and associated uncertainties into specifications for AISI's red teams and evaluation teams - identifying the tests that would provide the most informative evidence about whether specific risk pathways are viable. Analyzing the effectiveness of mitigations - such as monitoring infrastructure, compute governance, deployment guidelines, or containment protocols - drawing on input from national security stakeholders, and assessing which risk pathways remain plausible once mitigations are in place. Collaborating and communicating with government and national security stakeholders to develop and implement possible interventions, in partnership. What we're looking for In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process. Required experience The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant. You may be a good fit if you have: Experience producing detailed threat models, risk analyses, safety cases, or similar structured analytical work - in AI safety, cybersecurity, national security, or another domain. A track record of published research or substantial written analysis demonstrating rigorous reasoning about complex, uncertain topics. Strong written communication: an ability to present complex technical arguments clearly to both technical and non technical audiences. Deep familiarity with cybersecurity and the ways in which it will be impacted by high capability AI agents; alternatively with the AI alignment and AI safety literature, including existing work on loss of control, deception, power seeking, scalable oversight, and AI control. A sense of mission, urgency, and responsibility for success. An ability to bring your own research ideas and work in a self directed way, while also collaborating effectively and prioritising team efforts over extensive solo work. Strong candidates may also have Hands on experience with large language models (e.g., training, fine tuning, evaluation, or red teaming), providing concrete understanding of current model capabilities and limitations. Familiarity with AI capability evaluations and benchmarking methodologies. Desire to (and experience with) improving teams through mentoring and feedback. Security clearance We have a preference for candidates eligible for UK government SC clearance which typically requires residence in the UK for the last 2 years. You may also be required to undergo Developed Vetting (DV). DV typically requires a longer period of UK residency (around 5 years). Other core requirements You should be able to spend at least 9 days per fortnight working with us. You should be willing to work from our office in London (Whitehall) at least 3 days/week. You should be UK based. What we offer Impact you couldn't have anywhere else Incredibly talented, mission driven and supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best resourced public interest research team focused on AI security. Resources & access Pre release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AI research and adjacent sciences. If you're talented and driven, you'll own important problems early. 5 days off learning and development, annual stipends for learning and development, and funding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office (cafes, food court, gym) or option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work from home equipment. At least 25 days' annual leave, 8 public holidays, extra team wide breaks and 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. Salary levels Level 3 - Total Package £65,000 - £75,000 (inclusive of a base salary £35,720 plus additional technical talent allowance of £29,280 - £39,280) Level 4 - Total Package £85,000 - £95,000 (inclusive of a base salary £42,495 plus additional technical talent allowance of £42,505 - £52,505) Level 5 - Total Package £105,000 - £115,000 (inclusive of a base salary £55,805 plus additional technical talent allowance of £49,195 - £59,195) Level 6 - Total Package £125,000 - £135,000 (inclusive of a base salary £68,770 plus additional technical talent allowance of £56,230 - £66,230) Level 7 - Total Package £145,000 (inclusive of a base salary £68,770 plus additional technical talent allowance of £76,230) Use of AI in applications Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use. Internal fraud database The Internal Fraud function of the Fraud, Error, Debt and Grants Function at the Cabinet Office processes details of civil servants who have been dismissed for committing internal fraud, or who would have been dismissed had they not resigned. The Cabinet Office receives the details from participating government organisations of civil servants who have been dismissed, or who would have been dismissed had they not resigned, for internal fraud. In instances such as this, civil servants are then banned for 5 years from further employment in the civil service . click apply for full job details
Mar 10, 2026
Full time
Agentic AI Risk Modelling and Mitigations London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is Sunday 8 March 2026, end of day, anywhere on Earth. Team description As AI systems grow more capable and autonomous, understanding how humans could lose the ability to oversee, correct, or shut down these systems becomes critical - as does identifying what we can do to prevent it. Risk models for AI agents (for example, loss of control risk models) remain far less developed than those in comparable domains like cybersecurity and chem bio, and practical mitigations remain underexplored (especially beyond traditional alignment and control work). AISI is building a new team to close this gap. The new Agentic AI Risk Modelling and Mitigations team will develop rigorous models of how agentic AI could cause harm, identifying practical mitigations with a focus on measures the UK government are well placed to implement. We will draw on expertise only available within government - especially the national security community - to develop risk models and mitigations far more developed than those in academia or industry. The hiring manager for this role is Benjamin Hilton; the team is advised by Geoffrey Irving. You'll collaborate closely with researchers across AISI's red teams, evaluation teams, and alignment team, as well as with government stakeholders. Your work will draw on empirical evidence from AISI's evaluations, along with the broader cybersecurity and ML literature to develop detailed and precise threat models and mitigations. You'll need to reason carefully about complex and uncertain scenarios and communicate findings clearly to both technical researchers and policy decision makers. Some projects may also involve hands on ML or cybersecurity work, in collaboration with government partners, to develop mitigations. We are open to hires at junior, senior, staff, and principal research scientist levels. We may also make an offer to particularly promising candidates with management experience to lead the workstream in a management role. Representative projects you might work on Developing detailed models of specific loss of control scenarios - such as deceptive alignment during internal deployment, or a long horizon agentic cyberattack - specifying their causal structure, key assumptions, and plausibility given current and projected AI capabilities and propensities. Translating risk models and associated uncertainties into specifications for AISI's red teams and evaluation teams - identifying the tests that would provide the most informative evidence about whether specific risk pathways are viable. Analyzing the effectiveness of mitigations - such as monitoring infrastructure, compute governance, deployment guidelines, or containment protocols - drawing on input from national security stakeholders, and assessing which risk pathways remain plausible once mitigations are in place. Collaborating and communicating with government and national security stakeholders to develop and implement possible interventions, in partnership. What we're looking for In accordance with the Civil Service Commission rules, the following list contains all selection criteria for the interview process. Required experience The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant. You may be a good fit if you have: Experience producing detailed threat models, risk analyses, safety cases, or similar structured analytical work - in AI safety, cybersecurity, national security, or another domain. A track record of published research or substantial written analysis demonstrating rigorous reasoning about complex, uncertain topics. Strong written communication: an ability to present complex technical arguments clearly to both technical and non technical audiences. Deep familiarity with cybersecurity and the ways in which it will be impacted by high capability AI agents; alternatively with the AI alignment and AI safety literature, including existing work on loss of control, deception, power seeking, scalable oversight, and AI control. A sense of mission, urgency, and responsibility for success. An ability to bring your own research ideas and work in a self directed way, while also collaborating effectively and prioritising team efforts over extensive solo work. Strong candidates may also have Hands on experience with large language models (e.g., training, fine tuning, evaluation, or red teaming), providing concrete understanding of current model capabilities and limitations. Familiarity with AI capability evaluations and benchmarking methodologies. Desire to (and experience with) improving teams through mentoring and feedback. Security clearance We have a preference for candidates eligible for UK government SC clearance which typically requires residence in the UK for the last 2 years. You may also be required to undergo Developed Vetting (DV). DV typically requires a longer period of UK residency (around 5 years). Other core requirements You should be able to spend at least 9 days per fortnight working with us. You should be willing to work from our office in London (Whitehall) at least 3 days/week. You should be UK based. What we offer Impact you couldn't have anywhere else Incredibly talented, mission driven and supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best resourced public interest research team focused on AI security. Resources & access Pre release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AI research and adjacent sciences. If you're talented and driven, you'll own important problems early. 5 days off learning and development, annual stipends for learning and development, and funding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office (cafes, food court, gym) or option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work from home equipment. At least 25 days' annual leave, 8 public holidays, extra team wide breaks and 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. Salary levels Level 3 - Total Package £65,000 - £75,000 (inclusive of a base salary £35,720 plus additional technical talent allowance of £29,280 - £39,280) Level 4 - Total Package £85,000 - £95,000 (inclusive of a base salary £42,495 plus additional technical talent allowance of £42,505 - £52,505) Level 5 - Total Package £105,000 - £115,000 (inclusive of a base salary £55,805 plus additional technical talent allowance of £49,195 - £59,195) Level 6 - Total Package £125,000 - £135,000 (inclusive of a base salary £68,770 plus additional technical talent allowance of £56,230 - £66,230) Level 7 - Total Package £145,000 (inclusive of a base salary £68,770 plus additional technical talent allowance of £76,230) Use of AI in applications Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance for more information on appropriate and inappropriate use. Internal fraud database The Internal Fraud function of the Fraud, Error, Debt and Grants Function at the Cabinet Office processes details of civil servants who have been dismissed for committing internal fraud, or who would have been dismissed had they not resigned. The Cabinet Office receives the details from participating government organisations of civil servants who have been dismissed, or who would have been dismissed had they not resigned, for internal fraud. In instances such as this, civil servants are then banned for 5 years from further employment in the civil service . click apply for full job details
Job Scope The Royal Society is a self-governing Fellowship of distinguished scientists drawn from all areas of science, technology, engineering, mathematics and medicine. The Society's fundamental purpose is to recognise, promote and support excellence in science and to encourage the development and use of science for the benefit of humanity. The Society has played a part in some of the most fundamental, significant and life-changing discoveries in scientific history and Royal Society scientists continue to make outstanding contributions to science across the wide breadth of research areas. The Scientific Programmes Team comprises four key programmes that both facilitate scientist to scientist communication and recognise and celebrate excellence in science. The programmes are: Scientific Meetings (UK-wide) as recommended by the Hooke committee Delivery of international meetings in collaboration with the International Affairs Team Medals and Awards programme including associated prize lectures Fellowship annual events programme This role supports the work of the Medals and Fellowship programmes and is focused on two areas: supporting the administration of the medals and awards programme, and supporting the Fellowship annual events programme. Attention to detail and administrative experience within a busy team is essential, as is an ability to quickly build strong working relationships with internal colleagues and external partners at all levels. The role requires excellent Excel spreadsheet knowledge and skills including the ability to pull and analyse data. The successful candidate will have strong attention to detail, demonstrate exceptional organisation and communication skills and be used to managing competing priorities and expectations. The post holder will also be expected to contribute to other projects and events outside their remit to support the team's activities as a whole, if required. The post holder will be subject to Disclosure and Barring Service (DBS) checks. Please note that we are unable to offer sponsorship for this role. Reports to : Scientific Programmes Manager, Fellowship and Medals Line manages : None Pay band : Band B Salary : £31,000 per annum Contract type : Fixed term contract until January 2027 Hours: 35 hours per week (including some out of hours working) Location: Carlton House Terrace, London, SW1Y 5AG with some hybrid working available Closing date for applications: Friday, 13 March :59 hours Interviews will be held: 23 March, 25 March and 26 March 2026
Mar 10, 2026
Full time
Job Scope The Royal Society is a self-governing Fellowship of distinguished scientists drawn from all areas of science, technology, engineering, mathematics and medicine. The Society's fundamental purpose is to recognise, promote and support excellence in science and to encourage the development and use of science for the benefit of humanity. The Society has played a part in some of the most fundamental, significant and life-changing discoveries in scientific history and Royal Society scientists continue to make outstanding contributions to science across the wide breadth of research areas. The Scientific Programmes Team comprises four key programmes that both facilitate scientist to scientist communication and recognise and celebrate excellence in science. The programmes are: Scientific Meetings (UK-wide) as recommended by the Hooke committee Delivery of international meetings in collaboration with the International Affairs Team Medals and Awards programme including associated prize lectures Fellowship annual events programme This role supports the work of the Medals and Fellowship programmes and is focused on two areas: supporting the administration of the medals and awards programme, and supporting the Fellowship annual events programme. Attention to detail and administrative experience within a busy team is essential, as is an ability to quickly build strong working relationships with internal colleagues and external partners at all levels. The role requires excellent Excel spreadsheet knowledge and skills including the ability to pull and analyse data. The successful candidate will have strong attention to detail, demonstrate exceptional organisation and communication skills and be used to managing competing priorities and expectations. The post holder will also be expected to contribute to other projects and events outside their remit to support the team's activities as a whole, if required. The post holder will be subject to Disclosure and Barring Service (DBS) checks. Please note that we are unable to offer sponsorship for this role. Reports to : Scientific Programmes Manager, Fellowship and Medals Line manages : None Pay band : Band B Salary : £31,000 per annum Contract type : Fixed term contract until January 2027 Hours: 35 hours per week (including some out of hours working) Location: Carlton House Terrace, London, SW1Y 5AG with some hybrid working available Closing date for applications: Friday, 13 March :59 hours Interviews will be held: 23 March, 25 March and 26 March 2026
Minton, Treharne & Davies
Cardiff, South Glamorgan
Consultant Scientist (Food and Agriculture) Background MTD is currently recruiting for a Consultant Scientist (Food and Agriculture) to join our consultancy team in Cardiff, United Kingdom. Job Description As a Consultant Scientist within MTD's food and agriculture consultancy team, you will develop the skills required to perform forensic investigations into safety and quality disputes on a variety of food and agricultural commodities. This will include extensive training in our Food Laboratory at our Head Office in Cardiff and attendance on site with experienced consultants to learn in the field. The disputes can arise throughout the supply chain and are undertaken for clients in the marine and insurance sectors, including international insurance companies, traders, manufacturers, suppliers, ship owners, P&I Clubs, claims handlers, loss adjusters and solicitors. Our clients appoint MTD to provide clear and independent technical advice into the cause of an incident and how the problem might best be mitigated. Investigations typically involve attendance at the site of anadvisor (often at very short notice) to gather evidence, oversee sampling, interview parties and manage high pressure, contentious situations. Further investigation may involve laboratory analysis of samples using routine international test methods or tailored methodologies to determine the root cause of an incident. Findings are compiled into a technical report for clients without a scientific background, and experts may be required to give evidence in court, arbitration or mediation. Example Work Develop and oversee appropriate sampling protocols to determine the extent of mycotoxin contamination. Conclude reliably the rate of heat damage to a consignment of soya beans in East Asia and appraise how such damage could be mitigated. Attend in Djibouti to investigate the cause of a fire to a consignment of bagged wheat flour. Investigate the cause and extent of an infestation to grain in silos and warehouses in the United Kingdom. Investigate the apparent increase in moisture content to a consignment of refined sugar in West Africa despite no signs of external wetting. Attend in Central America to investigate the allegation, cause and extent in the change of colour of a consignment of maize. Investigate to determine the nature and source of a particulate contamination to a consignment of vegetable oils refined in Indonesia. Determine the cause of increased acidity of refined vegetable oil intended for use as a biofuel feedstock. Key Responsibilities Attend incidents worldwide to perform forensic investigations into safety and quality disputes concerning food and agricultural commodities. Prepare sampling and testing protocols for consignments in line with International Standards. Witness and supervise sampling operations. Gather contemporaneous evidence related to the background and circumstances of the incident. Review and consult documentation время researching applicable standards and regulations where required. Manage cases by reporting to clients and liaising with other parties involved in the incident. Prepare written technical advice and reports. Attend meetings with clients to discuss findings. Provide expert evidenceynn in mediation, arbitration or court. MTD's Requirements Postgraduate degree in a relevant subject preferred but not essential. Excellent verbal and written communication skills, including preparing scientific reports for non scientific clients. Problem solving skills and initiative. Eagerness to learn and develop skills. Prepared to travel at immediate notice. Ability to manage own workloadanda meet deadlines when handling multiple projects. Experience in the food industry or agricultural science is advantageous. Experience with sampling or analysing food and agricultural commodities would be considered an advantage. Company registered in England, Company No.
Mar 10, 2026
Full time
Consultant Scientist (Food and Agriculture) Background MTD is currently recruiting for a Consultant Scientist (Food and Agriculture) to join our consultancy team in Cardiff, United Kingdom. Job Description As a Consultant Scientist within MTD's food and agriculture consultancy team, you will develop the skills required to perform forensic investigations into safety and quality disputes on a variety of food and agricultural commodities. This will include extensive training in our Food Laboratory at our Head Office in Cardiff and attendance on site with experienced consultants to learn in the field. The disputes can arise throughout the supply chain and are undertaken for clients in the marine and insurance sectors, including international insurance companies, traders, manufacturers, suppliers, ship owners, P&I Clubs, claims handlers, loss adjusters and solicitors. Our clients appoint MTD to provide clear and independent technical advice into the cause of an incident and how the problem might best be mitigated. Investigations typically involve attendance at the site of anadvisor (often at very short notice) to gather evidence, oversee sampling, interview parties and manage high pressure, contentious situations. Further investigation may involve laboratory analysis of samples using routine international test methods or tailored methodologies to determine the root cause of an incident. Findings are compiled into a technical report for clients without a scientific background, and experts may be required to give evidence in court, arbitration or mediation. Example Work Develop and oversee appropriate sampling protocols to determine the extent of mycotoxin contamination. Conclude reliably the rate of heat damage to a consignment of soya beans in East Asia and appraise how such damage could be mitigated. Attend in Djibouti to investigate the cause of a fire to a consignment of bagged wheat flour. Investigate the cause and extent of an infestation to grain in silos and warehouses in the United Kingdom. Investigate the apparent increase in moisture content to a consignment of refined sugar in West Africa despite no signs of external wetting. Attend in Central America to investigate the allegation, cause and extent in the change of colour of a consignment of maize. Investigate to determine the nature and source of a particulate contamination to a consignment of vegetable oils refined in Indonesia. Determine the cause of increased acidity of refined vegetable oil intended for use as a biofuel feedstock. Key Responsibilities Attend incidents worldwide to perform forensic investigations into safety and quality disputes concerning food and agricultural commodities. Prepare sampling and testing protocols for consignments in line with International Standards. Witness and supervise sampling operations. Gather contemporaneous evidence related to the background and circumstances of the incident. Review and consult documentation время researching applicable standards and regulations where required. Manage cases by reporting to clients and liaising with other parties involved in the incident. Prepare written technical advice and reports. Attend meetings with clients to discuss findings. Provide expert evidenceynn in mediation, arbitration or court. MTD's Requirements Postgraduate degree in a relevant subject preferred but not essential. Excellent verbal and written communication skills, including preparing scientific reports for non scientific clients. Problem solving skills and initiative. Eagerness to learn and develop skills. Prepared to travel at immediate notice. Ability to manage own workloadanda meet deadlines when handling multiple projects. Experience in the food industry or agricultural science is advantageous. Experience with sampling or analysing food and agricultural commodities would be considered an advantage. Company registered in England, Company No.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Overview Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen. Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Team 90 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first-principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Diego Protas - Director of Engineering Diego, an expert in distributed systems and hardware architecture, merging physical computing with enterprise-scale infrastructure. Previously directing teams of 170+ engineers at Mercado Libre and orchestrating large-scale ML-based inference at Meta. At Relay, Diego's infectious enthusiasm and hands-on leadership are redefining the boundaries of speed and reliability. Tech Stack Highlights Python, Rust and TypeScript - we keep things simple but use the right tool for the job Cross-platform Flutter apps with a deep focus on user experience Cloud-native on GCP with extensive use of BigQuery and Cloud Run Extensive use of ML modelling and LLM inference - no gimmicks here, this is our daily routine Emerging tech integrations, including robotics and IoT-powered operations The Opportunity As a Software Engineer at Relay, you'll: Own challenging, impactful problems end-to-end, from routing algorithms to real-time optimisation services and intuitive operational tools. Collaborate closely with top engineers, data scientists, and product leaders in a highly autonomous and impact-driven environment. Regularly ship production-quality code weekly-and often daily-seeing your work directly impact Relay's growth. Create incredible product experiences powering the fastest-growing e-commerce platforms, including Vinted, TikTok, and Temu, impacting millions of users worldwide. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min API Integration Interview - 1 hour Technical Interview - 2 hours Operating Principles & Impact - 1 hour Decision and offer within 48 hours; our process mirrors our pace of work, typically completed in a week. Compensation, Benefits & Workplace Generous equity, richer than 99% of European startups, with annual top-ups to share Relay's success. Private health & dental coverage, so comprehensive you'd need to be a partner at a Magic Circle law firm to match it. 25 days of holidays Enhanced parental leave Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote. Hardware of your choice Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more). Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
Mar 10, 2026
Full time
Overview Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen. Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Team 90 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first-principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Diego Protas - Director of Engineering Diego, an expert in distributed systems and hardware architecture, merging physical computing with enterprise-scale infrastructure. Previously directing teams of 170+ engineers at Mercado Libre and orchestrating large-scale ML-based inference at Meta. At Relay, Diego's infectious enthusiasm and hands-on leadership are redefining the boundaries of speed and reliability. Tech Stack Highlights Python, Rust and TypeScript - we keep things simple but use the right tool for the job Cross-platform Flutter apps with a deep focus on user experience Cloud-native on GCP with extensive use of BigQuery and Cloud Run Extensive use of ML modelling and LLM inference - no gimmicks here, this is our daily routine Emerging tech integrations, including robotics and IoT-powered operations The Opportunity As a Software Engineer at Relay, you'll: Own challenging, impactful problems end-to-end, from routing algorithms to real-time optimisation services and intuitive operational tools. Collaborate closely with top engineers, data scientists, and product leaders in a highly autonomous and impact-driven environment. Regularly ship production-quality code weekly-and often daily-seeing your work directly impact Relay's growth. Create incredible product experiences powering the fastest-growing e-commerce platforms, including Vinted, TikTok, and Temu, impacting millions of users worldwide. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min API Integration Interview - 1 hour Technical Interview - 2 hours Operating Principles & Impact - 1 hour Decision and offer within 48 hours; our process mirrors our pace of work, typically completed in a week. Compensation, Benefits & Workplace Generous equity, richer than 99% of European startups, with annual top-ups to share Relay's success. Private health & dental coverage, so comprehensive you'd need to be a partner at a Magic Circle law firm to match it. 25 days of holidays Enhanced parental leave Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote. Hardware of your choice Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more). Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 10, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Sustainable Packaging - Paper & Coatings Scientist page is loaded Sustainable Packaging - Paper & Coatings Scientistlocations: Port Sunlight Research Labtime type: Full timeposted on: Posted 8 Days Agotime left to apply: End Date: March 11, 2026 (4 days left to apply)job requisition id: R- Job Title: Sustainable Packaging - Paper & Coatings Scientist Location: Port Sunlight Research Lab JOB PURPOSE We are looking for a creative, dedicated and ambitious individual with experience in coatings and/or paper engineering/science to join our team at Unilever's One Packaging R&D Centre. The Centre enables and accelerates the creation of novel packaging solutions to help meet Unilever's packaging ambitions and completely revolutionize our packaging with a particular focus on our flexibles portfolio . It is the place where future scientific leaders of the business are created. We are a high-performing, diverse and inclusive team of dynamic entrepreneurial people with a strong scientific background, courage and curiosity, and passion for sustainability and delivery that will have a positive impact on the planet. RESPONSIBILITIES As part of our world-class 'Future Packaging Technologies' team, you will play a key role in the flexibles packaging program, delivering new technologies and insights that will support the delivery of affordable superior paper-based solutions across Unilever's packaging portfolio. The key accountabilities for the role holder are as follows: • Support the selection, application, and optimization of inks, coatings, and overprint varnishes on flexible substrates to meet performance and sustainability requirements. • Assess and help interpret the physical, chemical, and surface properties of fiber based and film substrates to ensure compatibility with coatings and printing solutions. • Contribute to coating and ink evaluation by applying established analytical and characterization approaches to assess adhesion, barrier behavior, durability, and overall performance. • Provide day to day technical support to the team, including sample preparation, test execution, data collection, and basic troubleshooting. • Support scale up activities from lab to pilot trials by preparing materials, assisting with trial execution, resolving routine issues, and documenting processing conditions. • Contribute to experimental design and project planning, helping to generate data based insights, hypotheses, and recommendations that advance program objectives and support claims or IP development. • Maintain high quality documentation, contribute to SOP creation, ensure reliable testing practices, and help prepare data packages for internal reviews, sustainability claims, or IP filings. • Engaging with external partners and suppliers to gather information or samples and support the evaluation of new technologies, while fostering strong relationships across the internal R&D community. • Plan and execute work with increasing autonomy, collaborating with program leaders to deliver activities aligned with project milestones. • Work with digital experts and use digital tools to support material selection, data interpretation, and process optimization. ALL ABOUT YOU We are looking for someone that shares our passion for innovation, applied material science and sustainability, and the drive to take our paper packaging portfolio to the next level. Our Packaging strategy is not just about understanding and developing new materials - it's about making smart decisions on how, when, and where to use them. You will be part of a multi-disciplinary project team ethos where everybody contributes to achieving the same goal. What you will bring: • A higher education qualification in Materials Science, Polymer Chemistry, Chemical Engineering, Packaging Science, Printing & Coating Technology, Paper Technology, or a closely related discipline • Experience in industrially relevant materials development and/or characterisation. • Working knowledge of coatings, inks, and overprint varnishes for fibre based and/or film substrates, with the ability to build deeper understanding of how application methods and substrate interactions influence performance, is highly desirable. • Practical experience working with coatings, inks, or overprint varnishes in a laboratory environment, and familiarity with fundamental characterisation approaches used to assess performance, is highly desirable. • Experience supporting scale up or pilot activities, including sample preparation, troubleshooting minor issues, and documenting processing conditions • Competent in the use of laboratory equipment and data analysis, with a proactive, problem solving approach and strong analytical skills for interpreting data and identifying business relevant insights. • Demonstrated ability to collaborate effectively with cross functional teams and to build constructive working relationships with internal and external partners to support project delivery. • Strong communication and presentation skills, with the ability to explain technical findings clearly to a range of audiences. • Must be creative, highly passionate, willing to think big and inspire both the team, stakeholders and customers. NOTES What We Offer Not only do we offer a competitive salary and pension scheme, we also offer an annual bonus, subsidised gym membership, a discounted staff shop and shares. You'll have the opportunity to work directly with our renowned and exciting brands in a flexible and hybrid working environment. Whilst the role is advertised on a full-time basis, we would be happy to discuss possible flexible working options and what this may look like for you. We are a key advocate of wellbeing and offer a variety of support for our people including hubs, programmes and development opportunities. We strive to achieve a family-friendly and inclusive workplace and to, above all, create possibilities for all. Diversity at Unilever is about inclusion, embracing differences, creating possibilities and growing together for better business performance. We embrace diversity in our workforce. This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity. We are also more than happy to provide reasonable adjustments during our application and interview process to enable you to be present your best self. To find out more, including about our Employee Resource Groups, please click here . Recruitment Fraud Cyber criminals advertise fake job adverts with prestigious employers as a way of stealing information or even defrauding individuals out of money. In the most sophisticated cases, they will set up fake websites, which have a similar address to companies like Unilever. They even conduct fake telephone interviews and then offer candidates a role with the proviso they pay a fee for background checks or to cover work visa costs. These types of attacks are becoming more common as more people are looking for employment in the economic climate. If you become aware of potential recruitment fraud, spot fake Unilever recruitment adverts or fake LinkedIn profiles, report them via Una Live Chat. Unilever does not accept responsibility or liability for any candidates who are financially impacted by recruitment fraud. Your vigilance is key!
Mar 10, 2026
Full time
Sustainable Packaging - Paper & Coatings Scientist page is loaded Sustainable Packaging - Paper & Coatings Scientistlocations: Port Sunlight Research Labtime type: Full timeposted on: Posted 8 Days Agotime left to apply: End Date: March 11, 2026 (4 days left to apply)job requisition id: R- Job Title: Sustainable Packaging - Paper & Coatings Scientist Location: Port Sunlight Research Lab JOB PURPOSE We are looking for a creative, dedicated and ambitious individual with experience in coatings and/or paper engineering/science to join our team at Unilever's One Packaging R&D Centre. The Centre enables and accelerates the creation of novel packaging solutions to help meet Unilever's packaging ambitions and completely revolutionize our packaging with a particular focus on our flexibles portfolio . It is the place where future scientific leaders of the business are created. We are a high-performing, diverse and inclusive team of dynamic entrepreneurial people with a strong scientific background, courage and curiosity, and passion for sustainability and delivery that will have a positive impact on the planet. RESPONSIBILITIES As part of our world-class 'Future Packaging Technologies' team, you will play a key role in the flexibles packaging program, delivering new technologies and insights that will support the delivery of affordable superior paper-based solutions across Unilever's packaging portfolio. The key accountabilities for the role holder are as follows: • Support the selection, application, and optimization of inks, coatings, and overprint varnishes on flexible substrates to meet performance and sustainability requirements. • Assess and help interpret the physical, chemical, and surface properties of fiber based and film substrates to ensure compatibility with coatings and printing solutions. • Contribute to coating and ink evaluation by applying established analytical and characterization approaches to assess adhesion, barrier behavior, durability, and overall performance. • Provide day to day technical support to the team, including sample preparation, test execution, data collection, and basic troubleshooting. • Support scale up activities from lab to pilot trials by preparing materials, assisting with trial execution, resolving routine issues, and documenting processing conditions. • Contribute to experimental design and project planning, helping to generate data based insights, hypotheses, and recommendations that advance program objectives and support claims or IP development. • Maintain high quality documentation, contribute to SOP creation, ensure reliable testing practices, and help prepare data packages for internal reviews, sustainability claims, or IP filings. • Engaging with external partners and suppliers to gather information or samples and support the evaluation of new technologies, while fostering strong relationships across the internal R&D community. • Plan and execute work with increasing autonomy, collaborating with program leaders to deliver activities aligned with project milestones. • Work with digital experts and use digital tools to support material selection, data interpretation, and process optimization. ALL ABOUT YOU We are looking for someone that shares our passion for innovation, applied material science and sustainability, and the drive to take our paper packaging portfolio to the next level. Our Packaging strategy is not just about understanding and developing new materials - it's about making smart decisions on how, when, and where to use them. You will be part of a multi-disciplinary project team ethos where everybody contributes to achieving the same goal. What you will bring: • A higher education qualification in Materials Science, Polymer Chemistry, Chemical Engineering, Packaging Science, Printing & Coating Technology, Paper Technology, or a closely related discipline • Experience in industrially relevant materials development and/or characterisation. • Working knowledge of coatings, inks, and overprint varnishes for fibre based and/or film substrates, with the ability to build deeper understanding of how application methods and substrate interactions influence performance, is highly desirable. • Practical experience working with coatings, inks, or overprint varnishes in a laboratory environment, and familiarity with fundamental characterisation approaches used to assess performance, is highly desirable. • Experience supporting scale up or pilot activities, including sample preparation, troubleshooting minor issues, and documenting processing conditions • Competent in the use of laboratory equipment and data analysis, with a proactive, problem solving approach and strong analytical skills for interpreting data and identifying business relevant insights. • Demonstrated ability to collaborate effectively with cross functional teams and to build constructive working relationships with internal and external partners to support project delivery. • Strong communication and presentation skills, with the ability to explain technical findings clearly to a range of audiences. • Must be creative, highly passionate, willing to think big and inspire both the team, stakeholders and customers. NOTES What We Offer Not only do we offer a competitive salary and pension scheme, we also offer an annual bonus, subsidised gym membership, a discounted staff shop and shares. You'll have the opportunity to work directly with our renowned and exciting brands in a flexible and hybrid working environment. Whilst the role is advertised on a full-time basis, we would be happy to discuss possible flexible working options and what this may look like for you. We are a key advocate of wellbeing and offer a variety of support for our people including hubs, programmes and development opportunities. We strive to achieve a family-friendly and inclusive workplace and to, above all, create possibilities for all. Diversity at Unilever is about inclusion, embracing differences, creating possibilities and growing together for better business performance. We embrace diversity in our workforce. This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity. We are also more than happy to provide reasonable adjustments during our application and interview process to enable you to be present your best self. To find out more, including about our Employee Resource Groups, please click here . Recruitment Fraud Cyber criminals advertise fake job adverts with prestigious employers as a way of stealing information or even defrauding individuals out of money. In the most sophisticated cases, they will set up fake websites, which have a similar address to companies like Unilever. They even conduct fake telephone interviews and then offer candidates a role with the proviso they pay a fee for background checks or to cover work visa costs. These types of attacks are becoming more common as more people are looking for employment in the economic climate. If you become aware of potential recruitment fraud, spot fake Unilever recruitment adverts or fake LinkedIn profiles, report them via Una Live Chat. Unilever does not accept responsibility or liability for any candidates who are financially impacted by recruitment fraud. Your vigilance is key!
