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.
At Morrisons, our Data, Analytics & AI team plays a vital role in driving decisions across the business by unlocking the power of our data. Whether it's enabling quick insight through self-serve tools like Looker or delivering deeper analysis through exploring the patterns in our data, we help teams across the business solve problems, drive performance, and create value. As a Data Science Manager, you'll lead a small but impactful team of data scientists and analysts, helping shape and deliver a roadmap of data science products and initiatives that align with our business goals. You'll work closely with stakeholders across the organisation to understand their challenges and apply cutting-edge analytics to solve them. This is a hands on role with technical delivery at its core, combined with leadership and strategic direction. What you'll be doing: Lead, mentor and develop a team of Data Scientists and Analysts, setting clear objectives and supporting professional growth Own the delivery of complex data science products and models that support strategic business objectives Shape and contribute to a 1-2 year data science roadmap, ensuring all work is aligned with business priorities and linked to core processes Embed a lean, value first culture, minimising waste and driving improvements in efficiency and EBITDA Champion data literacy and promote best practice in analytical thinking across the business Translate business problems into analytical approaches, delivering insights that inform action Support the team with hands on technical tasks where required, including coding and modelling Collaborate with Data Engineering and other teams to ensure the right data is available and accessible About you What we're looking for: A strategic thinker with experience solving complex business problems through data Strong communication and storytelling skills. Able to bring data to life for non technical audiences An inclusive and motivating leader, with experience mentoring others and creating high performing teams Comfortable working in both Agile and Waterfall environments Inquisitive mindset - always looking to challenge the status quo and improve ways of working Excellent stakeholder management skills, with the ability to gather and refine requirements to ensure value delivery Key Skills: Expert level SQL skills, extracting and transforming data with speed and accuracy Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred About us In return for all your hard work, you will receive: 15% discount in store from the day you join us Additional 10% discount card for a friend or family member Annual bonus scheme Career progression and development opportunities Generous holiday entitlement Market leading pension scheme and life assurance Healthcare benefits including Aviva Digital GP 'MyPerks' giving you discount with over 850 retailers Free parking onsite Enhanced Family, Maternity and Paternity Leave Private Healthcare Car Allowance (company car provided in some instances) Alive with activity, our modern Head Office is home to our corporate teams that make sure everything runs smoothly. Here, you'll find comfy breakout areas, a coffee shop, Morrisons Daily and a subsidised restaurant. We are within commuting distance of Leeds, Manchester and the Yorkshire Dales - and we even have free parking! At our Head Office you will expect to find supplier showcases, charity fundraising and celebrations all year round for the events that mean the most to our colleagues. There's more to our business as it's fast paced and ever changing, as such we've got lots of fresh opportunities for you to play your part in our success. We'd love to meet you! At Morrisons, we're proud to be building a team that reflects the diversity of the communities we serve. We want every colleague to feel respected, supported and able to be themselves at work. Different voices, experiences and ways of thinking help us grow and improve and that's good for our customers too. We're always looking for people from all walks of life to join us and bring their talents to our team. Together, we can build a workplace where everyone has the chance to thrive, make a difference and belong.
Mar 10, 2026
Full time
At Morrisons, our Data, Analytics & AI team plays a vital role in driving decisions across the business by unlocking the power of our data. Whether it's enabling quick insight through self-serve tools like Looker or delivering deeper analysis through exploring the patterns in our data, we help teams across the business solve problems, drive performance, and create value. As a Data Science Manager, you'll lead a small but impactful team of data scientists and analysts, helping shape and deliver a roadmap of data science products and initiatives that align with our business goals. You'll work closely with stakeholders across the organisation to understand their challenges and apply cutting-edge analytics to solve them. This is a hands on role with technical delivery at its core, combined with leadership and strategic direction. What you'll be doing: Lead, mentor and develop a team of Data Scientists and Analysts, setting clear objectives and supporting professional growth Own the delivery of complex data science products and models that support strategic business objectives Shape and contribute to a 1-2 year data science roadmap, ensuring all work is aligned with business priorities and linked to core processes Embed a lean, value first culture, minimising waste and driving improvements in efficiency and EBITDA Champion data literacy and promote best practice in analytical thinking across the business Translate business problems into analytical approaches, delivering insights that inform action Support the team with hands on technical tasks where required, including coding and modelling Collaborate with Data Engineering and other teams to ensure the right data is available and accessible About you What we're looking for: A strategic thinker with experience solving complex business problems through data Strong communication and storytelling skills. Able to bring data to life for non technical audiences An inclusive and motivating leader, with experience mentoring others and creating high performing teams Comfortable working in both Agile and Waterfall environments Inquisitive mindset - always looking to challenge the status quo and improve ways of working Excellent stakeholder management skills, with the ability to gather and refine requirements to ensure value delivery Key Skills: Expert level SQL skills, extracting and transforming data with speed and accuracy Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred About us In return for all your hard work, you will receive: 15% discount in store from the day you join us Additional 10% discount card for a friend or family member Annual bonus scheme Career progression and development opportunities Generous holiday entitlement Market leading pension scheme and life assurance Healthcare benefits including Aviva Digital GP 'MyPerks' giving you discount with over 850 retailers Free parking onsite Enhanced Family, Maternity and Paternity Leave Private Healthcare Car Allowance (company car provided in some instances) Alive with activity, our modern Head Office is home to our corporate teams that make sure everything runs smoothly. Here, you'll find comfy breakout areas, a coffee shop, Morrisons Daily and a subsidised restaurant. We are within commuting distance of Leeds, Manchester and the Yorkshire Dales - and we even have free parking! At our Head Office you will expect to find supplier showcases, charity fundraising and celebrations all year round for the events that mean the most to our colleagues. There's more to our business as it's fast paced and ever changing, as such we've got lots of fresh opportunities for you to play your part in our success. We'd love to meet you! At Morrisons, we're proud to be building a team that reflects the diversity of the communities we serve. We want every colleague to feel respected, supported and able to be themselves at work. Different voices, experiences and ways of thinking help us grow and improve and that's good for our customers too. We're always looking for people from all walks of life to join us and bring their talents to our team. Together, we can build a workplace where everyone has the chance to thrive, make a difference and belong.
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.
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.
The Applications team within R&D supports Lubrizol through the invention and synthesis of new speciality-chemicals and technical support of existing products. We are looking for a motivated scientist to join our Applications team and work in a laboratory and use their technical expertise to evaluate new additives in composites materials by interpreting and analysing analytical and performance data. The ideal candidate will have experience working in an application laboratory evaluating new materials. This role is based at Hexagon Tower, Blackley Manchester located in a suburban setting, four miles from Manchester City Centre, UK. Salary competitive dependent upon skills and experience, plus excellent benefits. In this role you will: Be a scientist leading the evaluation of composite materials, developing your own ideas for analysis and proposing new test methods for mechanical testing experiments. Be "hands on" in the laboratory formulating new composite materials, moulding and curing coupons then undertaking physical testing. Decide how testing should proceed using logic, experience, and creativity to meet agreed timelines. Manage laboratory assets and keeping equipment serviced and calibrated, develop good relationship with suppliers to ensure best practice in instrumentation. Be part of a wider research team support the laboratory initiatives and follow safe laboratory practices Document, interpret and communicate results to colleagues and internal project sponsors. Attend industry conferences and present scientific data when relevant Travel to other countries may be important for developing regional labs. The ideal candidate will have: PhD in materials science or related discipline. BSc or equivalent in chemistry with five years experience in a materials testing laboratory Ability to apply scientific understanding to experiment planning Good communication, team working and interpersonal skills, to be successful in a multidisciplinary environment Good project management skills, with experience of managing multiple projects to deadlines Good IT skills especially a knowledge of data science tools Job Segment: Research Scientist, Materials Science, Senior Scientist, Laboratory, Chemistry, Science
Mar 10, 2026
Full time
The Applications team within R&D supports Lubrizol through the invention and synthesis of new speciality-chemicals and technical support of existing products. We are looking for a motivated scientist to join our Applications team and work in a laboratory and use their technical expertise to evaluate new additives in composites materials by interpreting and analysing analytical and performance data. The ideal candidate will have experience working in an application laboratory evaluating new materials. This role is based at Hexagon Tower, Blackley Manchester located in a suburban setting, four miles from Manchester City Centre, UK. Salary competitive dependent upon skills and experience, plus excellent benefits. In this role you will: Be a scientist leading the evaluation of composite materials, developing your own ideas for analysis and proposing new test methods for mechanical testing experiments. Be "hands on" in the laboratory formulating new composite materials, moulding and curing coupons then undertaking physical testing. Decide how testing should proceed using logic, experience, and creativity to meet agreed timelines. Manage laboratory assets and keeping equipment serviced and calibrated, develop good relationship with suppliers to ensure best practice in instrumentation. Be part of a wider research team support the laboratory initiatives and follow safe laboratory practices Document, interpret and communicate results to colleagues and internal project sponsors. Attend industry conferences and present scientific data when relevant Travel to other countries may be important for developing regional labs. The ideal candidate will have: PhD in materials science or related discipline. BSc or equivalent in chemistry with five years experience in a materials testing laboratory Ability to apply scientific understanding to experiment planning Good communication, team working and interpersonal skills, to be successful in a multidisciplinary environment Good project management skills, with experience of managing multiple projects to deadlines Good IT skills especially a knowledge of data science tools Job Segment: Research Scientist, Materials Science, Senior Scientist, Laboratory, Chemistry, Science
Introduction Echo Labs is building the scientific, and technical foundation for ecological intelligence: a multimodal system to measure, model, and forecast Ecosystem Condition as a dynamic property. We are a collaborative and interdisciplinary team of scientists and engineers engaged in a planetary moonshot - with a public good mission, operating like a start up. We are a new Focused Research Organization (FRO) supported by Convergent Research and funded by the Advanced Research and Invention Agency to pursue high-risk, high-reward science in the public interest. About this role The Chief Science Officer (CSO) anchors this effort in scientific rigour, ecological credibility, and long-term legitimacy and plays a decisive role in ensuring that this infrastructure is scientifically sound and transformative. The CSO is responsible for ensuring that Echo's data, models, and interpretations faithfully reflect state-of-the-art ecological science while enabling bold, operational innovation. This role bridges fundamental ecology, field methods, and applied modelling, translating ecological theory into scalable, decision-grade infrastructure. This is a high-leverage role: you'll lead Echo's ecology vertical and relationship with the ecology community. The CSO reports to the CEO and works in close partnership with the Chief Technology Officer and Director of Product & Partnerships as a core member of Echo's executive leadership team. Core Responsibilities Conceptual Framework: Own and continuously refine Echo's scientific framing of Ecosystem Condition, grounded in ECT+/SEEA typologies and current ecological theory. Ensure scientific defensibility, interpretability, and transparency of Echo's outputs for the academic community, policymakers, and external partners. Set standards for scientific validation, benchmarking, and uncertainty characterisation across the programme. Data Strategy and Analytical Direction: Lead the identification, evaluation, and strategic use of existing ecological and Earth-observation datasets, determining when external data can accelerate progress versus when new data generation is essential. Set the analytical direction for how existing datasets are integrated, stress-tested, or rejected, including defining appropriate benchmarks, comparators, and limitations. Guide early in-silico analyses to inform sampling design, modelling priorities, and go/no-go decisions, ensuring resources are focused on data and approaches with the highest scientific leverage. Establish criteria for reuse, interoperability, and alignment of legacy datasets with Echo's Ecosystem Condition framework, avoiding dependence on datasets that are ecologically misaligned or methodologically brittle. Ecological Data Generation: Lead scientific oversight of Echo's sampling architecture, ensuring ecological sensitivity and robustness. Guide methodological choices across in-situ data streams (eDNA, acoustics, vegetation structure, soil health, hydrology, etc.). Oversee ecological QA/QC, signal separability testing, and temporal sensitivity to disturbance and recovery. Modelling Integration and Ecological Interpretability: Work hand-in-hand with the CTO and ML leads to ensure ecological meaning is preserved in latent representations ("ecosystem fingerprints") and predictive models. Validate that modelling choices align with ecological processes, scales, and constraints rather than spurious correlations. Champion explainability and ecological interpretability of model outputs. Scientific Leadership, Governance and External Engagement: Act as Echo's senior scientific representative to the ecological research community. Build trust and adoption through workshops, advisory engagement, and transparent publication of methods, data, and results. Shape Echo's contribution to emerging standards in ecological monitoring, modelling, and data governance. Interface with the Science Advisory Board, translating feedback into operational scientific decisions. Progression. In six months you will have Established an internal scientific definition of Ecosystem Condition, aligned with ECT+/SEEA and explicitly scoped to what Echo will and will not measure. Audited existing ecological data to identify usable signals, inferable dynamics, and critical gaps, guiding early go/no-go decisions on new data collection. Set clear priorities for early models and metrics, focusing on a small number of high-leverage downstream tasks rather than solving everything at once. Designed an initial metric and model architecture, including decisions on single vs. multi-layer representations and a strategy for ecological interpretability. Led internal and external scientific workshops to align sampling, modelling, and core scientific questions, resulting in shared buy-in and a v1 sampling design. Produced foundational scientific artifacts, including a v1 Ecosystem Condition framework, data-to-signal mapping, interpretability plan, and a scientific risk register. We Offer (Amazing Benefits) A rare chance to build institutional architecture for frontier science and work with some of the smartest and most talented experts from different fields. Up to a 6% employer pension contribution, with optional additional salary sacrifice, because future-you deserves comfort. Top-tier private medical and dental insurance-are fully covered for you and your dependents. Stay healthy, my friend. Generous parental leave-20 weeks make-whole-pay for both parents. 25 days of holiday allowance. Wellness allowance for fitness and wellness activities. Profile (You Are) PhD (or equivalent) in ecology, ecosystem science, environmental science, or a closely related field. Deep understanding of ecosystem functioning, resilience, or biodiversity dynamics, ideally across multiple spatial scales. Familiarity with ecological modelling, including interaction with machine learning. Strong basis in advanced statistical methods. Proven background in rigorous experimental design. Demonstrated experience designing, interpreting, or overseeing field-based ecological data collection. Track record of interdisciplinary collaboration across ecology, data science, and engineering. Exceptional scientific judgement and communication skills, with the ability to translate complexity into clarity. Highly organised and outcome-focused, with experience structuring workplans, prioritising trade-offs, and driving progress across interdisciplinary teams under time and resource constraints. Highly Valued Experience Experience working with multimodal ecological datasets (e.g. combining field data with Earth observation). Prior involvement in large-scale or national ecological monitoring programmes. Experience engaging with policy, regulatory, or applied decision-making contexts. Familiarity with FAIR + CARE data principles or ecological data governance. Leadership roles in collaborative or mission-driven research initiatives. Demonstrated ability to translate scientific vision into delivered products or platforms, with experience taking complex research programmes from concept through execution against clear timelines and milestones. Track record of operating in delivery-oriented environments (e.g. research infrastructure builds, applied science programmes, or mission-driven organisations) where scientific ambition is matched with disciplined execution. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 100000 - 130000 GBP a year Title commensurate with experience: CSO / Director of Ecological research Bonus: Performance-based
Mar 10, 2026
Full time
Introduction Echo Labs is building the scientific, and technical foundation for ecological intelligence: a multimodal system to measure, model, and forecast Ecosystem Condition as a dynamic property. We are a collaborative and interdisciplinary team of scientists and engineers engaged in a planetary moonshot - with a public good mission, operating like a start up. We are a new Focused Research Organization (FRO) supported by Convergent Research and funded by the Advanced Research and Invention Agency to pursue high-risk, high-reward science in the public interest. About this role The Chief Science Officer (CSO) anchors this effort in scientific rigour, ecological credibility, and long-term legitimacy and plays a decisive role in ensuring that this infrastructure is scientifically sound and transformative. The CSO is responsible for ensuring that Echo's data, models, and interpretations faithfully reflect state-of-the-art ecological science while enabling bold, operational innovation. This role bridges fundamental ecology, field methods, and applied modelling, translating ecological theory into scalable, decision-grade infrastructure. This is a high-leverage role: you'll lead Echo's ecology vertical and relationship with the ecology community. The CSO reports to the CEO and works in close partnership with the Chief Technology Officer and Director of Product & Partnerships as a core member of Echo's executive leadership team. Core Responsibilities Conceptual Framework: Own and continuously refine Echo's scientific framing of Ecosystem Condition, grounded in ECT+/SEEA typologies and current ecological theory. Ensure scientific defensibility, interpretability, and transparency of Echo's outputs for the academic community, policymakers, and external partners. Set standards for scientific validation, benchmarking, and uncertainty characterisation across the programme. Data Strategy and Analytical Direction: Lead the identification, evaluation, and strategic use of existing ecological and Earth-observation datasets, determining when external data can accelerate progress versus when new data generation is essential. Set the analytical direction for how existing datasets are integrated, stress-tested, or rejected, including defining appropriate benchmarks, comparators, and limitations. Guide early in-silico analyses to inform sampling design, modelling priorities, and go/no-go decisions, ensuring resources are focused on data and approaches with the highest scientific leverage. Establish criteria for reuse, interoperability, and alignment of legacy datasets with Echo's Ecosystem Condition framework, avoiding dependence on datasets that are ecologically misaligned or methodologically brittle. Ecological Data Generation: Lead scientific oversight of Echo's sampling architecture, ensuring ecological sensitivity and robustness. Guide methodological choices across in-situ data streams (eDNA, acoustics, vegetation structure, soil health, hydrology, etc.). Oversee ecological QA/QC, signal separability testing, and temporal sensitivity to disturbance and recovery. Modelling Integration and Ecological Interpretability: Work hand-in-hand with the CTO and ML leads to ensure ecological meaning is preserved in latent representations ("ecosystem fingerprints") and predictive models. Validate that modelling choices align with ecological processes, scales, and constraints rather than spurious correlations. Champion explainability and ecological interpretability of model outputs. Scientific Leadership, Governance and External Engagement: Act as Echo's senior scientific representative to the ecological research community. Build trust and adoption through workshops, advisory engagement, and transparent publication of methods, data, and results. Shape Echo's contribution to emerging standards in ecological monitoring, modelling, and data governance. Interface with the Science Advisory Board, translating feedback into operational scientific decisions. Progression. In six months you will have Established an internal scientific definition of Ecosystem Condition, aligned with ECT+/SEEA and explicitly scoped to what Echo will and will not measure. Audited existing ecological data to identify usable signals, inferable dynamics, and critical gaps, guiding early go/no-go decisions on new data collection. Set clear priorities for early models and metrics, focusing on a small number of high-leverage downstream tasks rather than solving everything at once. Designed an initial metric and model architecture, including decisions on single vs. multi-layer representations and a strategy for ecological interpretability. Led internal and external scientific workshops to align sampling, modelling, and core scientific questions, resulting in shared buy-in and a v1 sampling design. Produced foundational scientific artifacts, including a v1 Ecosystem Condition framework, data-to-signal mapping, interpretability plan, and a scientific risk register. We Offer (Amazing Benefits) A rare chance to build institutional architecture for frontier science and work with some of the smartest and most talented experts from different fields. Up to a 6% employer pension contribution, with optional additional salary sacrifice, because future-you deserves comfort. Top-tier private medical and dental insurance-are fully covered for you and your dependents. Stay healthy, my friend. Generous parental leave-20 weeks make-whole-pay for both parents. 25 days of holiday allowance. Wellness allowance for fitness and wellness activities. Profile (You Are) PhD (or equivalent) in ecology, ecosystem science, environmental science, or a closely related field. Deep understanding of ecosystem functioning, resilience, or biodiversity dynamics, ideally across multiple spatial scales. Familiarity with ecological modelling, including interaction with machine learning. Strong basis in advanced statistical methods. Proven background in rigorous experimental design. Demonstrated experience designing, interpreting, or overseeing field-based ecological data collection. Track record of interdisciplinary collaboration across ecology, data science, and engineering. Exceptional scientific judgement and communication skills, with the ability to translate complexity into clarity. Highly organised and outcome-focused, with experience structuring workplans, prioritising trade-offs, and driving progress across interdisciplinary teams under time and resource constraints. Highly Valued Experience Experience working with multimodal ecological datasets (e.g. combining field data with Earth observation). Prior involvement in large-scale or national ecological monitoring programmes. Experience engaging with policy, regulatory, or applied decision-making contexts. Familiarity with FAIR + CARE data principles or ecological data governance. Leadership roles in collaborative or mission-driven research initiatives. Demonstrated ability to translate scientific vision into delivered products or platforms, with experience taking complex research programmes from concept through execution against clear timelines and milestones. Track record of operating in delivery-oriented environments (e.g. research infrastructure builds, applied science programmes, or mission-driven organisations) where scientific ambition is matched with disciplined execution. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 100000 - 130000 GBP a year Title commensurate with experience: CSO / Director of Ecological research Bonus: Performance-based
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.
Lead Data & AI Scientist Hybrid: 1-2 days per week in the office (London) Permanent £100k-£150k DOE + Bonus + Benefits Experis are delighted to be partnering with a leading and well-respected organisation as they continue to invest heavily in Data Science, Artificial Intelligence and Generative AI click apply for full job details
Mar 10, 2026
Full time
Lead Data & AI Scientist Hybrid: 1-2 days per week in the office (London) Permanent £100k-£150k DOE + Bonus + Benefits Experis are delighted to be partnering with a leading and well-respected organisation as they continue to invest heavily in Data Science, Artificial Intelligence and Generative AI click apply for full job details
Head of Data Science Salary: £115K - £125K + bonus Location: Manchester 2-4 days a month The Opportunity We're working with a high-growth business that is scaling its data function to the next level. Data scientists here have traditionally combined reporting with predictive modelling, but the business is now creating a dedicated leadership role to bring focus, structure and engineering rigour to the d click apply for full job details
Mar 10, 2026
Full time
Head of Data Science Salary: £115K - £125K + bonus Location: Manchester 2-4 days a month The Opportunity We're working with a high-growth business that is scaling its data function to the next level. Data scientists here have traditionally combined reporting with predictive modelling, but the business is now creating a dedicated leadership role to bring focus, structure and engineering rigour to the d click apply for full job details
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
Arcinova , A Quotient Sciences Company, is dedicated to providing innovative contract research, development, and manufacturing services. We offer a comprehensive range of integrated specialist services for early stage drug development, underpinned by strong industry knowledge and scientific expertise. Our mission is to bring science, innovation, and collaboration together to overcome the barriers in drug development. We empower emerging biotechs and large pharma alike to bring life-changing therapies to patients faster, through an efficient, effective approach focused on quality, science, and innovation. Our vision is to advance progress through science, delivering solutions that make a measurable difference. We look ahead with purpose, driven to shape a smarter, more resilient future for all. The Role We are looking for an Analytical Scientist to join our team in Alnwick on permanent basis. In this role, you will develop, validate and apply analytical methodologies to support pharmaceutical development and manufacturing, while ensuring compliance with GLP/GMP guidelines. Key Responsibilities Analysis of drug substances, raw materials, intermediates and drug products using a variety of analytical techniques. Develop, validate and report analytical methodology and, where appropriate, provide resolution to technical problems Apply analytical methodologies during the quality control and stability evaluation of a range of materials Prepare work protocols for approval, critically assess data generated and review data from peers Prepare and review reports, quality documents and training documentation Acquire/record data in a manner that complies with GxP and internal policies/procedures Perform assigned roles within Quality Control such as equipment responsible operator, training, equipment hardware and/or software validation and the ordering of consumable items Work with due regard to health and safety of self and others Work flexibly across the site to meet business needs. Qualifications and experience required for competent performance BSc (Hons) or equivalent in a relevant scientific discipline. Experience in the application of analytical methodologies in a pharmaceutical environment is advantageous. Good written and oral communication skills The ability to critically assess data and have a flexible approach to new work challenges Competent in the use of Microsoft Office packages such as Word and Excel. Eligibility to Work in the UK Please note that this position is not eligible for sponsorship under the UK points-based immigration system. If you require sponsorship, we will be unable to progress your application or make an offer of employment. As this is a permanent role, we are also unable to accept applications from candidates on a Graduate Visa. Application Requirements When applying for a position with Quotient Sciences to be able to work in our organization you must be aged 18 years or over and not have been debarred by the FDA. If you indicate you are under the age of 18 or have been debarred then your application will be automatically declined. Our Commitment to Diversity, Equity and Inclusion Quotient Sciences are advocates for positive change and conscious inclusion. We strive to create a diverse Quotient workforce and develop a workplace culture that provides a sense of acceptance for every person within our organization. As a global employer, we recognize the value in having an organization that is a true reflection and representation of our society today. Specifically we will not discriminate on the basis of race, color, creed, religion, gender, gender identity, pregnancy, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage or citizenship status, veteran or military status, disability, medical condition, genetic information, caregiver status, unemployment status or any other characteristic prohibited by federal, state and/or local laws. This applies to all aspects of employment, including hiring, promotion, demotion, compensation, training, working conditions, transfer, job assignments, benefits, layoff, and termination.
Mar 10, 2026
Full time
Arcinova , A Quotient Sciences Company, is dedicated to providing innovative contract research, development, and manufacturing services. We offer a comprehensive range of integrated specialist services for early stage drug development, underpinned by strong industry knowledge and scientific expertise. Our mission is to bring science, innovation, and collaboration together to overcome the barriers in drug development. We empower emerging biotechs and large pharma alike to bring life-changing therapies to patients faster, through an efficient, effective approach focused on quality, science, and innovation. Our vision is to advance progress through science, delivering solutions that make a measurable difference. We look ahead with purpose, driven to shape a smarter, more resilient future for all. The Role We are looking for an Analytical Scientist to join our team in Alnwick on permanent basis. In this role, you will develop, validate and apply analytical methodologies to support pharmaceutical development and manufacturing, while ensuring compliance with GLP/GMP guidelines. Key Responsibilities Analysis of drug substances, raw materials, intermediates and drug products using a variety of analytical techniques. Develop, validate and report analytical methodology and, where appropriate, provide resolution to technical problems Apply analytical methodologies during the quality control and stability evaluation of a range of materials Prepare work protocols for approval, critically assess data generated and review data from peers Prepare and review reports, quality documents and training documentation Acquire/record data in a manner that complies with GxP and internal policies/procedures Perform assigned roles within Quality Control such as equipment responsible operator, training, equipment hardware and/or software validation and the ordering of consumable items Work with due regard to health and safety of self and others Work flexibly across the site to meet business needs. Qualifications and experience required for competent performance BSc (Hons) or equivalent in a relevant scientific discipline. Experience in the application of analytical methodologies in a pharmaceutical environment is advantageous. Good written and oral communication skills The ability to critically assess data and have a flexible approach to new work challenges Competent in the use of Microsoft Office packages such as Word and Excel. Eligibility to Work in the UK Please note that this position is not eligible for sponsorship under the UK points-based immigration system. If you require sponsorship, we will be unable to progress your application or make an offer of employment. As this is a permanent role, we are also unable to accept applications from candidates on a Graduate Visa. Application Requirements When applying for a position with Quotient Sciences to be able to work in our organization you must be aged 18 years or over and not have been debarred by the FDA. If you indicate you are under the age of 18 or have been debarred then your application will be automatically declined. Our Commitment to Diversity, Equity and Inclusion Quotient Sciences are advocates for positive change and conscious inclusion. We strive to create a diverse Quotient workforce and develop a workplace culture that provides a sense of acceptance for every person within our organization. As a global employer, we recognize the value in having an organization that is a true reflection and representation of our society today. Specifically we will not discriminate on the basis of race, color, creed, religion, gender, gender identity, pregnancy, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage or citizenship status, veteran or military status, disability, medical condition, genetic information, caregiver status, unemployment status or any other characteristic prohibited by federal, state and/or local laws. This applies to all aspects of employment, including hiring, promotion, demotion, compensation, training, working conditions, transfer, job assignments, benefits, layoff, and termination.
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.
Lead Data Scientist Salary: Up to £75,000 + competitive benefits Location: Leicester. 2 days onsite per week A major UK retailer is hiring a Lead Data Scientist to shape how £160M of digital marketing spend is measured, optimised and scaled. This role sits at the centre of marketing, data and commercial strategy. You will lead a small team and own the analytical frameworks used to measure performance
Mar 10, 2026
Full time
Lead Data Scientist Salary: Up to £75,000 + competitive benefits Location: Leicester. 2 days onsite per week A major UK retailer is hiring a Lead Data Scientist to shape how £160M of digital marketing spend is measured, optimised and scaled. This role sits at the centre of marketing, data and commercial strategy. You will lead a small team and own the analytical frameworks used to measure performance
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.
