Senior ML Engineer, Generative AI Innovation Center Job ID: AWS EMEA SARL (Poland Branch) The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an Senior ML Engineer on our team, you will work with clients, partners and other AWS teams to drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS's custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients. As an Amazonian leader you will demonstrate the Amazon Leadership Principles, coaching and mentoring others on best practices, performance and career development. You must be comfortable leading others and driving work, rather than being part of the team. If you love to learn and want to innovate in the world of generative AI, Generative AI Innovation and Delivery is the right place for you. Key job responsibilities • Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF) • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions • Define path to production for generative AI solutions and implement large scale production generative AI solutions. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS • 5+ years of professional software development and machine learning experience • Proficiency in at least one programming language • Experience mentoring engineers, leading technical initiatives, or managing an engineering team • Hands-on experience with deep learning and machine learning methods (e.g., for training, fine tuning, and inference) • Experience with design, development, optimization and productionization of generative AI solutions, algorithms, or technologies PREFERRED QUALIFICATIONS • Bachelor's degree in Computer Science or equivalent • Hands-on experience with at least one ML library or framework • 2+ years of professional experience in developing, deploying or optimizing ML models in production • 5+ years of professional experience in the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: March 7, 2025 (Updated about 2 months ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Jul 24, 2025
Full time
Senior ML Engineer, Generative AI Innovation Center Job ID: AWS EMEA SARL (Poland Branch) The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an Senior ML Engineer on our team, you will work with clients, partners and other AWS teams to drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS's custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients. As an Amazonian leader you will demonstrate the Amazon Leadership Principles, coaching and mentoring others on best practices, performance and career development. You must be comfortable leading others and driving work, rather than being part of the team. If you love to learn and want to innovate in the world of generative AI, Generative AI Innovation and Delivery is the right place for you. Key job responsibilities • Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF) • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions • Define path to production for generative AI solutions and implement large scale production generative AI solutions. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS • 5+ years of professional software development and machine learning experience • Proficiency in at least one programming language • Experience mentoring engineers, leading technical initiatives, or managing an engineering team • Hands-on experience with deep learning and machine learning methods (e.g., for training, fine tuning, and inference) • Experience with design, development, optimization and productionization of generative AI solutions, algorithms, or technologies PREFERRED QUALIFICATIONS • Bachelor's degree in Computer Science or equivalent • Hands-on experience with at least one ML library or framework • 2+ years of professional experience in developing, deploying or optimizing ML models in production • 5+ years of professional experience in the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: March 7, 2025 (Updated about 2 months ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Senior Machine Learning Scientist (Viator) London, England, United Kingdom About Viator Viator, a Tripadvisor company, is the leading marketplace for travel experiences. We believethat making memories is what travel is all about. And with 300,000+ travel experiences toexplore-everything from simple tours to extreme adventures (and all the niche, interesting stuffin between)-making memories that will last a lifetime has never been easier. With industry-leading flexibility and last-minute availability, it's never too late to make any day extraordinary.Viator. One app, 300,000+ travel experiences you'll remember. Perks of Working at Viator Competitive compensation packages (routinely benchmarked against the latest industry data), including base salary and annual bonus. "Work your way" with flexibility to suit your lifestyle. Viator takes a remote-friendly approach to collaboration across a worldwide team, with the option to join on-site as often as you'd like. Flexible schedule. Work-life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching. Give back? Give more! We match qualifying charitable donations annually. Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks. We believe that travel is employee development, so we provide discounts and more. Employee assistance program. We're here for you with resources and programs to help you through life's challenges. Health benefits. We offer great coverage and competitive premiums. Our Values We aspire to lead. Tap into your talent, ambition, and knowledge to bring us - and you - to new heights. We're relentlessly curious. We push beyond the usual, the known, the "that's just how it's done." We're better together. We learn from, accept, respect, support, and value one another- and are creating something remarkable in the process. We serve our customers, always. We listen, question, respond, and strive for wow moments. We strive for better, not perfect. We won't get it right the first time - or every time. We'll provide a safe environment in which to make mistakes, iterate, improve, and grow. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique identities, abilities, and experiences, so we can collectively revolutionize travel and together find the good out there. You will work on: Design, code, experiment and implement models and algorithms to enhance customer satisfaction, increase supplier value, optimize business results, and ensure infrastructure efficiency. Analyse large datasets including daily customer events, product, destination, supplier and pricing info, extracting key insights to spur innovation and improvement. Collaborate with product managers and various business stakeholders to ensure top-quality outcomes to meet internal objectives. Investigate and adopt innovative concepts that offer tangible benefits. Employ techniques like Deep Learning, Bayesian Modelling, Large Language Models, Product embedding, Recommendation Systems, and Computer Vision. To be successful in the role, you'll need: 5+ years of hands-on data science experience. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Awareness of current ML techniques, keen on self-improvement and striving to solve real-world data challenges. Strong skills in SQL and at least one programming language. Experience in ML model productization and a grasp of MLOps. To be comfortable in code reviews, discussing architecture, and collaborating with a multidisciplinary team for regular model deployments. Experience in deploying online solutions and analysing real-time results through A/B testing. To be passionate about mentoring junior members of the team, and have a strong desire to help us perform to the best of our ability. Leadership qualities, autonomy, and team collaboration skills. Clear communication skills, awareness of the audience, and proactive sharing of findings. Actively involved in business networking and able to communicate complex ideas across the business simply and effectively. Desired qualifications: Master's or PhD in Computer Science, Operations Research, Statistics, or related quantitative disciplines. Knowledge in Large Language Models (LLM), dynamic pricing, image processing, or recommendation systems. Prior experience in e-commerce or at an Online Travel Agency. Job Location: This role offers flexibility, allowing you to work either on-site hybrid or remotely from the UK, Poland, or Portugal. Occasional travel to company offices may be required If you need a reasonable accommodation or support during the application or the recruiting process due to a medical condition or disability, please reach out to your individual recruiter or send an email and let us know the nature of your request. Please include the job requisition number in your message. Apply for this job indicates a required field First Name Last Name Preferred First Name Email Phone Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf
Jul 24, 2025
Full time
Senior Machine Learning Scientist (Viator) London, England, United Kingdom About Viator Viator, a Tripadvisor company, is the leading marketplace for travel experiences. We believethat making memories is what travel is all about. And with 300,000+ travel experiences toexplore-everything from simple tours to extreme adventures (and all the niche, interesting stuffin between)-making memories that will last a lifetime has never been easier. With industry-leading flexibility and last-minute availability, it's never too late to make any day extraordinary.Viator. One app, 300,000+ travel experiences you'll remember. Perks of Working at Viator Competitive compensation packages (routinely benchmarked against the latest industry data), including base salary and annual bonus. "Work your way" with flexibility to suit your lifestyle. Viator takes a remote-friendly approach to collaboration across a worldwide team, with the option to join on-site as often as you'd like. Flexible schedule. Work-life balance is ingrained in our culture by design. Trust and accountability make it work. Donation matching. Give back? Give more! We match qualifying charitable donations annually. Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs. Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you. Travel perks. We believe that travel is employee development, so we provide discounts and more. Employee assistance program. We're here for you with resources and programs to help you through life's challenges. Health benefits. We offer great coverage and competitive premiums. Our Values We aspire to lead. Tap into your talent, ambition, and knowledge to bring us - and you - to new heights. We're relentlessly curious. We push beyond the usual, the known, the "that's just how it's done." We're better together. We learn from, accept, respect, support, and value one another- and are creating something remarkable in the process. We serve our customers, always. We listen, question, respond, and strive for wow moments. We strive for better, not perfect. We won't get it right the first time - or every time. We'll provide a safe environment in which to make mistakes, iterate, improve, and grow. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique identities, abilities, and experiences, so we can collectively revolutionize travel and together find the good out there. You will work on: Design, code, experiment and implement models and algorithms to enhance customer satisfaction, increase supplier value, optimize business results, and ensure infrastructure efficiency. Analyse large datasets including daily customer events, product, destination, supplier and pricing info, extracting key insights to spur innovation and improvement. Collaborate with product managers and various business stakeholders to ensure top-quality outcomes to meet internal objectives. Investigate and adopt innovative concepts that offer tangible benefits. Employ techniques like Deep Learning, Bayesian Modelling, Large Language Models, Product embedding, Recommendation Systems, and Computer Vision. To be successful in the role, you'll need: 5+ years of hands-on data science experience. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Awareness of current ML techniques, keen on self-improvement and striving to solve real-world data challenges. Strong skills in SQL and at least one programming language. Experience in ML model productization and a grasp of MLOps. To be comfortable in code reviews, discussing architecture, and collaborating with a multidisciplinary team for regular model deployments. Experience in deploying online solutions and analysing real-time results through A/B testing. To be passionate about mentoring junior members of the team, and have a strong desire to help us perform to the best of our ability. Leadership qualities, autonomy, and team collaboration skills. Clear communication skills, awareness of the audience, and proactive sharing of findings. Actively involved in business networking and able to communicate complex ideas across the business simply and effectively. Desired qualifications: Master's or PhD in Computer Science, Operations Research, Statistics, or related quantitative disciplines. Knowledge in Large Language Models (LLM), dynamic pricing, image processing, or recommendation systems. Prior experience in e-commerce or at an Online Travel Agency. Job Location: This role offers flexibility, allowing you to work either on-site hybrid or remotely from the UK, Poland, or Portugal. Occasional travel to company offices may be required If you need a reasonable accommodation or support during the application or the recruiting process due to a medical condition or disability, please reach out to your individual recruiter or send an email and let us know the nature of your request. Please include the job requisition number in your message. Apply for this job indicates a required field First Name Last Name Preferred First Name Email Phone Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf
Job ID: Amazon Development Center (Tel Aviv) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Are you an inventive, curious, and driven Applied Scientist with a strong background in AI and Deep Learning? Join Amazon's AWS Multimodal generative AI science team and be a catalyst for groundbreaking advancements in Computer Vision, Generative AI, and foundational models. As part of the AWS Multimodal generative AI science team, you'll lead innovative research projects, develop state-of-the-art algorithms, and pioneer solutions that will directly impact millions of Amazon customers. Leveraging Amazon's vast computing power, you'll work alongside a supportive and diverse group of top-tier scientists and engineers, contributing to products that redefine the industry. Key job responsibilities: Lead research initiatives in Multimodal generative AI, pushing the boundaries of model efficiency, accuracy, and scalability. Design, implement, and evaluate deep learning models in a production environment. Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation. Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture: Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. BASIC QUALIFICATIONS Ph.D. or Master's in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field. Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms. Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java). First author in research publications in peer-reviewed conferences or journals. PREFERRED QUALIFICATIONS Experience designing and leading complex research projects from ideation to implementation. Deep understanding of statistical modeling, optimization, and algorithm development. Excellent communication skills, with the ability to convey complex technical information to diverse audiences.
Jul 24, 2025
Full time
Job ID: Amazon Development Center (Tel Aviv) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Are you an inventive, curious, and driven Applied Scientist with a strong background in AI and Deep Learning? Join Amazon's AWS Multimodal generative AI science team and be a catalyst for groundbreaking advancements in Computer Vision, Generative AI, and foundational models. As part of the AWS Multimodal generative AI science team, you'll lead innovative research projects, develop state-of-the-art algorithms, and pioneer solutions that will directly impact millions of Amazon customers. Leveraging Amazon's vast computing power, you'll work alongside a supportive and diverse group of top-tier scientists and engineers, contributing to products that redefine the industry. Key job responsibilities: Lead research initiatives in Multimodal generative AI, pushing the boundaries of model efficiency, accuracy, and scalability. Design, implement, and evaluate deep learning models in a production environment. Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation. Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture: Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve. BASIC QUALIFICATIONS Ph.D. or Master's in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field. Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms. Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java). First author in research publications in peer-reviewed conferences or journals. PREFERRED QUALIFICATIONS Experience designing and leading complex research projects from ideation to implementation. Deep understanding of statistical modeling, optimization, and algorithm development. Excellent communication skills, with the ability to convey complex technical information to diverse audiences.
Job ID: Amazon Development Centre (London) Limited At Amazon, we're revolutionizing the future of shopping with Rufus, our AI-driven shopping assistant. We're seeking an exceptional Senior Applied Scientist with a strong machine learning, NLP and Gen AI background with relevant industry experience to join our Rufus Features Science team in London. You will work at the intersection of the latest research and real-world impact, pushing the boundaries of agentic AI, multimodal language technology, leveraging RAG and RL, to create unparalleled shopping experiences. As a Senior Applied Scientist, you'll be at the forefront of developing state-of-the-art, conversation-based, agentic, multimodal shopping experiences. You will leverage the latest advancements in Multimodal and Visual Large Language Models (MLLMs/VLMs), and AI Agents to transform how customers discover, research, and purchase products. As a Senior Applied Scientist at Amazon, you'll set the standard for scientific excellence, make decisions that influence our algorithm and architecture development, and drive innovation in agentic MLLM technology. Your work will directly enhance how customers interact with our platform, making product discovery and purchasing more intuitive, efficient, and personalized. If you're passionate about pushing the boundaries of AI, thrive in solving complex problems, and want to make a significant impact on the e-commerce industry, we want to hear from you. Key job responsibilities Lead the development of state-of-the-art agentic LLM solutions for conversational shopping, considering scalability, latency, and quality. Design and implement innovative AI technologies that push the boundaries of Natural Language Processing (NLP), Generative AI, MLLMs/VLMs, Machine Learning (ML), Retrieval-Augmented Generation (RAG), and Reinforcement Learning (RL). Lead science roadmaps spanning multiple areas, working with senior leaders and stakeholders. Develop and evaluate production Agentic AI systems for real customer use cases, focusing on LLM-based conversational interfaces and multimodal interactions. Drive end-to-end MLLM projects with high ambiguity, scale, and complexity, taking a hands-on approach to the most critical aspects. Collaborate with cross-functional teams to rapidly bring new research into production, directly impacting millions of customers. Communicate progress and results internally to both technical and non-technical audiences and publish at top-tier conferences. About the team You will be part of the Rufus Features Science team based in London, working alongside over 100 engineers, designers and product managers, focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding multimodal user queries to planning and generating MLLM responses that combine text, image, audio and video. BASIC QUALIFICATIONS - PhD - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with neural deep learning methods and machine learning - Experience in building machine learning models for business application - PhD in NLP, Information Retrieval, Machine Learning, or related fields (or equivalent experience), with 6+ years of industry experience. - Extensive experience with deep learning-based NLP, IR, and MLLM/VLM methods. - Strong track record in addressing real-world problems using ML and NLP. - Expertise in developing and owning production ML models and systems, particularly those involving LLMs. - Proficiency in Python and experience with production-level implementation. - Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. - Familiarity with cloud computing platforms, particularly AWS. - Demonstrated ability to lead and shape scientific roadmaps across multiple areas, collaborating with product, science, and engineering managers. - Knowledge of recent advancements in AI agents, including multi-agent systems and agent evaluation frameworks. PREFERRED QUALIFICATIONS - Experience with popular deep learning frameworks such as MxNet and Tensor Flow. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Good publication record at top-tier venues such as ACL, NAACL, EMNLP, SIGIR, ICLR, NeurIPS, or similar. - Understanding of e-commerce and recommendation systems. - Excellent communication skills, solid work ethic, and a strong desire to write production-quality code. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Jul 24, 2025
Full time
Job ID: Amazon Development Centre (London) Limited At Amazon, we're revolutionizing the future of shopping with Rufus, our AI-driven shopping assistant. We're seeking an exceptional Senior Applied Scientist with a strong machine learning, NLP and Gen AI background with relevant industry experience to join our Rufus Features Science team in London. You will work at the intersection of the latest research and real-world impact, pushing the boundaries of agentic AI, multimodal language technology, leveraging RAG and RL, to create unparalleled shopping experiences. As a Senior Applied Scientist, you'll be at the forefront of developing state-of-the-art, conversation-based, agentic, multimodal shopping experiences. You will leverage the latest advancements in Multimodal and Visual Large Language Models (MLLMs/VLMs), and AI Agents to transform how customers discover, research, and purchase products. As a Senior Applied Scientist at Amazon, you'll set the standard for scientific excellence, make decisions that influence our algorithm and architecture development, and drive innovation in agentic MLLM technology. Your work will directly enhance how customers interact with our platform, making product discovery and purchasing more intuitive, efficient, and personalized. If you're passionate about pushing the boundaries of AI, thrive in solving complex problems, and want to make a significant impact on the e-commerce industry, we want to hear from you. Key job responsibilities Lead the development of state-of-the-art agentic LLM solutions for conversational shopping, considering scalability, latency, and quality. Design and implement innovative AI technologies that push the boundaries of Natural Language Processing (NLP), Generative AI, MLLMs/VLMs, Machine Learning (ML), Retrieval-Augmented Generation (RAG), and Reinforcement Learning (RL). Lead science roadmaps spanning multiple areas, working with senior leaders and stakeholders. Develop and evaluate production Agentic AI systems for real customer use cases, focusing on LLM-based conversational interfaces and multimodal interactions. Drive end-to-end MLLM projects with high ambiguity, scale, and complexity, taking a hands-on approach to the most critical aspects. Collaborate with cross-functional teams to rapidly bring new research into production, directly impacting millions of customers. Communicate progress and results internally to both technical and non-technical audiences and publish at top-tier conferences. About the team You will be part of the Rufus Features Science team based in London, working alongside over 100 engineers, designers and product managers, focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding multimodal user queries to planning and generating MLLM responses that combine text, image, audio and video. BASIC QUALIFICATIONS - PhD - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with neural deep learning methods and machine learning - Experience in building machine learning models for business application - PhD in NLP, Information Retrieval, Machine Learning, or related fields (or equivalent experience), with 6+ years of industry experience. - Extensive experience with deep learning-based NLP, IR, and MLLM/VLM methods. - Strong track record in addressing real-world problems using ML and NLP. - Expertise in developing and owning production ML models and systems, particularly those involving LLMs. - Proficiency in Python and experience with production-level implementation. - Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. - Familiarity with cloud computing platforms, particularly AWS. - Demonstrated ability to lead and shape scientific roadmaps across multiple areas, collaborating with product, science, and engineering managers. - Knowledge of recent advancements in AI agents, including multi-agent systems and agent evaluation frameworks. PREFERRED QUALIFICATIONS - Experience with popular deep learning frameworks such as MxNet and Tensor Flow. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Good publication record at top-tier venues such as ACL, NAACL, EMNLP, SIGIR, ICLR, NeurIPS, or similar. - Understanding of e-commerce and recommendation systems. - Excellent communication skills, solid work ethic, and a strong desire to write production-quality code. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Why Harvey Harvey is a secure AI platform for legal and professional services that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized and developed by our expert team of lawyers, engineers and research scientists. We've found product market fit and are scaling our team very quickly. Some reasons to join Harvey are: Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world, including Paul Weiss , A&O Shearman , Ashurst , O'Melveny & Myers, PwC , KKR, and many others. Strategic investors: Raised over $500 million from strategic investors including Sequoia, Google Ventures, Kleiner Perkins, and OpenAI. World-class team: Harvey is hiring the best talent from DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Glean, Superhuman, Figma, and more. Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services. Performance: 4x ARR in 2024. Competitive compensation. Role Overview As an Enterprise Customer Success Manager, you'll play a critical role in guiding our clients through their journey with Harvey, and help define the future of work at top enterprises and leading Law Firms. This position is pivotal in ensuring our clients not only adopt but also derive maximum value from our technology. You'll act as a trusted advisor, deeply integrating Harvey into their business processes and workflows. What You'll Do Strategic Implementation: Lead the integration of Harvey into client workflows, ensuring seamless adoption and optimal use of our AI solutions. Training & Enablement: Evangelize the power of LLMs as you meet with and enable end users to adopt Harvey on a daily-basis as it becomes a "must have" product. Client Relationship Management: Serve as the primary contact for clients with a prescriptive and consultative approach and serving as a thought partner to deliver a superior customer experience. Success Metrics Management: Leverage adoption rates, utilization metrics, and other KPIs to drive strategies ensuring client satisfaction and high ROI. Advocacy and Engagement: Encourage user and stakeholder engagement, transforming them into Harvey advocates within their organizations. Customer Health Monitoring: Use analytics and feedback to maintain customer satisfaction, ensuring readiness for renewal and expansion opportunities. Feedback Loop: Relay client insights back to our internal teams, aiding in the continuous improvement of our product and services. What You Have Experienced professionals with a background in Enterprise SaaS, legal (big law) or top tier management consulting firms and direct experience managing large-scale technology projects. Individuals with excellent communication and strategic planning skills, capable of influencing stakeholders at various levels. Results driven candidates who are able to ruthlessly prioritize competing tasks and demanding customers seamlessly Team players described as committed, collaborative and proactive with a team-first mentality. What We Offer A chance to be at the forefront of AI technology and innovation, directly impacting how our clients' businesses operate and thrive. An opportunity to contribute to the growth and direction of our rapidly-evolving Customer Success program, building out best-in-class playbooks and processes. A collaborative work environment that promotes growth, learning, and development. Please find our UK applicant privacy notice here . Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are in the early innings of a generational company. Joining early at a hypergrowth startup has proven to lead to exponential growth in responsibility, access, and ability. Apply here today!
Jul 24, 2025
Full time
Why Harvey Harvey is a secure AI platform for legal and professional services that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized and developed by our expert team of lawyers, engineers and research scientists. We've found product market fit and are scaling our team very quickly. Some reasons to join Harvey are: Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world, including Paul Weiss , A&O Shearman , Ashurst , O'Melveny & Myers, PwC , KKR, and many others. Strategic investors: Raised over $500 million from strategic investors including Sequoia, Google Ventures, Kleiner Perkins, and OpenAI. World-class team: Harvey is hiring the best talent from DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Glean, Superhuman, Figma, and more. Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services. Performance: 4x ARR in 2024. Competitive compensation. Role Overview As an Enterprise Customer Success Manager, you'll play a critical role in guiding our clients through their journey with Harvey, and help define the future of work at top enterprises and leading Law Firms. This position is pivotal in ensuring our clients not only adopt but also derive maximum value from our technology. You'll act as a trusted advisor, deeply integrating Harvey into their business processes and workflows. What You'll Do Strategic Implementation: Lead the integration of Harvey into client workflows, ensuring seamless adoption and optimal use of our AI solutions. Training & Enablement: Evangelize the power of LLMs as you meet with and enable end users to adopt Harvey on a daily-basis as it becomes a "must have" product. Client Relationship Management: Serve as the primary contact for clients with a prescriptive and consultative approach and serving as a thought partner to deliver a superior customer experience. Success Metrics Management: Leverage adoption rates, utilization metrics, and other KPIs to drive strategies ensuring client satisfaction and high ROI. Advocacy and Engagement: Encourage user and stakeholder engagement, transforming them into Harvey advocates within their organizations. Customer Health Monitoring: Use analytics and feedback to maintain customer satisfaction, ensuring readiness for renewal and expansion opportunities. Feedback Loop: Relay client insights back to our internal teams, aiding in the continuous improvement of our product and services. What You Have Experienced professionals with a background in Enterprise SaaS, legal (big law) or top tier management consulting firms and direct experience managing large-scale technology projects. Individuals with excellent communication and strategic planning skills, capable of influencing stakeholders at various levels. Results driven candidates who are able to ruthlessly prioritize competing tasks and demanding customers seamlessly Team players described as committed, collaborative and proactive with a team-first mentality. What We Offer A chance to be at the forefront of AI technology and innovation, directly impacting how our clients' businesses operate and thrive. An opportunity to contribute to the growth and direction of our rapidly-evolving Customer Success program, building out best-in-class playbooks and processes. A collaborative work environment that promotes growth, learning, and development. Please find our UK applicant privacy notice here . Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are in the early innings of a generational company. Joining early at a hypergrowth startup has proven to lead to exponential growth in responsibility, access, and ability. Apply here today!
Sr. Applied Scientist, Trustworthy Shopping Experience (TSE) Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As a Senior Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities - You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives. - You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc. - Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined. - You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. - You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones. - You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members. - You set standards and proactively drive components to use and improve on state-of-the-art techniques. - You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals. BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with conducting research in a corporate setting - Experience in patents or publications at top-tier peer-reviewed conferences or journals. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
Jul 24, 2025
Full time
Sr. Applied Scientist, Trustworthy Shopping Experience (TSE) Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As a Senior Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities - You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives. - You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc. - Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined. - You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. - You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones. - You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members. - You set standards and proactively drive components to use and improve on state-of-the-art techniques. - You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals. BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with conducting research in a corporate setting - Experience in patents or publications at top-tier peer-reviewed conferences or journals. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
At Hudl, we build great teams. We hire the best of the best to ensure you're working with people you can constantly learn from. You're trusted to get your work done your way while testing the limits of what's possible and what's next. We work hard to provide a culture where everyone feels supported, and our employees feel it-their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces . We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That's why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role We're looking for an Engineering Manager to join our Applied Machine Learning team and deliver new experiences and valuable insights to our coaches, athletes and fans across Hudl. You'll drive game-changing initiatives that use cutting-edge computer vision and deep learning at scale to shape the future of sports, from professional teams to local high schools. At Hudl, Engineering Managers: Deliver for customers. You'll independently manage your multidisciplinary team of 5 to 10 Engineers and Data Scientists, ensuring quarterly and annual goals are met while supporting their efforts to deliver high-impact results for customers and the business. Collaborate . You'll work closely with other teams and leaders to deliver your projects in small increments, resolve your cross-team dependencies, and ensure our products meet the highest standards. Be the technical example. You'll set high standards for architecture, code quality, and system health, while guiding your team in building resilient, cost-effective solutions that contribute to Hudl's long-term success. Cultivate an empowered environment. You'll build and maintain an environment where your team is supported, engaged, and able to operate at their highest potential. You'll optimize across technology, people and process to create a high-performing, scalable team that consistently delivers results. Hire and develop top talent . You'll provide technical and career development guidance to Applied Scientists and Engineers across the organization. For this role, we're currently considering candidates who live within a commuting distance of our office in London. But with our flexible work policy, there aren't any current requirements for the number of days you come to the office. Must-Haves Leadership experience. In previous roles, you've supported a team of 5-10 individual contributors to operate at their highest potential. System expertise . You've built, maintained and monitored complex AI/ML models and systems in production at scale. Strong technical proficiency. You have extensive experience in several of the following areas: machine vision (classical and deep learning), multi-view geometry, GPU accelerators, inference on edge devices, LLM's models, real-time systems, and signal processing. Communication skills. You have excellent verbal and written communication, with the ability to clearly convey complex technical concepts and trade-offs across all levels of the organization and to cross-functional stakeholders. A proven track record . You know how to focus on products, delivering impactful AI/ML products through close collaboration with partners. Nice-to-Haves Sports industry experience . If you've used AI/ML in sports to generate data and/or create insights, that's a plus. Our Role Champion work-life harmony . We'll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too. Guarantee autonomy . We have an open, honest culture and we trust our people from day one. Your team will support you, but you'll own your work and have the agency to try new ideas. Encourage career growth. We're lifelong learners who encourage professional development. We'll give you tons of resources and opportunities to keep growing. Provide an environment to help you succeed . We've invested in our offices, designing incredible spaces with our employees in mind. But whether you're at the office or working remotely, we'll provide you the tech you need to do your best work. Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees-but no matter where you're located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health. Inclusion at Hudl Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we'll create an environment where everyone, no matter their differences, feels like they belong. We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities . But we recognize there's ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports . We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates. Please don't hesitate to apply-we'd love to hear from you. Privacy Policy Hudl Applicant and Candidate Privacy Policy
Jul 23, 2025
Full time
At Hudl, we build great teams. We hire the best of the best to ensure you're working with people you can constantly learn from. You're trusted to get your work done your way while testing the limits of what's possible and what's next. We work hard to provide a culture where everyone feels supported, and our employees feel it-their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces . We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That's why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role We're looking for an Engineering Manager to join our Applied Machine Learning team and deliver new experiences and valuable insights to our coaches, athletes and fans across Hudl. You'll drive game-changing initiatives that use cutting-edge computer vision and deep learning at scale to shape the future of sports, from professional teams to local high schools. At Hudl, Engineering Managers: Deliver for customers. You'll independently manage your multidisciplinary team of 5 to 10 Engineers and Data Scientists, ensuring quarterly and annual goals are met while supporting their efforts to deliver high-impact results for customers and the business. Collaborate . You'll work closely with other teams and leaders to deliver your projects in small increments, resolve your cross-team dependencies, and ensure our products meet the highest standards. Be the technical example. You'll set high standards for architecture, code quality, and system health, while guiding your team in building resilient, cost-effective solutions that contribute to Hudl's long-term success. Cultivate an empowered environment. You'll build and maintain an environment where your team is supported, engaged, and able to operate at their highest potential. You'll optimize across technology, people and process to create a high-performing, scalable team that consistently delivers results. Hire and develop top talent . You'll provide technical and career development guidance to Applied Scientists and Engineers across the organization. For this role, we're currently considering candidates who live within a commuting distance of our office in London. But with our flexible work policy, there aren't any current requirements for the number of days you come to the office. Must-Haves Leadership experience. In previous roles, you've supported a team of 5-10 individual contributors to operate at their highest potential. System expertise . You've built, maintained and monitored complex AI/ML models and systems in production at scale. Strong technical proficiency. You have extensive experience in several of the following areas: machine vision (classical and deep learning), multi-view geometry, GPU accelerators, inference on edge devices, LLM's models, real-time systems, and signal processing. Communication skills. You have excellent verbal and written communication, with the ability to clearly convey complex technical concepts and trade-offs across all levels of the organization and to cross-functional stakeholders. A proven track record . You know how to focus on products, delivering impactful AI/ML products through close collaboration with partners. Nice-to-Haves Sports industry experience . If you've used AI/ML in sports to generate data and/or create insights, that's a plus. Our Role Champion work-life harmony . We'll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too. Guarantee autonomy . We have an open, honest culture and we trust our people from day one. Your team will support you, but you'll own your work and have the agency to try new ideas. Encourage career growth. We're lifelong learners who encourage professional development. We'll give you tons of resources and opportunities to keep growing. Provide an environment to help you succeed . We've invested in our offices, designing incredible spaces with our employees in mind. But whether you're at the office or working remotely, we'll provide you the tech you need to do your best work. Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees-but no matter where you're located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health. Inclusion at Hudl Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we'll create an environment where everyone, no matter their differences, feels like they belong. We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities . But we recognize there's ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports . We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates. Please don't hesitate to apply-we'd love to hear from you. Privacy Policy Hudl Applicant and Candidate Privacy Policy
Job Description Join the Chief Data & Analytics Office (CDAO) at JPMorgan Chase and be part of a team that accelerates the firm's data and analytics journey. We focus on ensuring data quality and security while leveraging insights to promote decision-making and support commercial goals through AI and machine learning. As an AI ML Lead Software Engineer within the Chief Data & Analytics Office, you will become part of a mission to modernize compliance through scalable and explainable AI. We are building a system that answers the question: "Can I use this data?", not with guesswork, but with prediction/classification, logic, proof, and intelligent automation. Our work sits at the intersection of applied machine learning, AI reasoning systems, and data governance. We are designing the triage layer of an intelligent decision engine that combines ML-driven classification, LLM-assisted parsing, and formal logic-based verification. This is an opportunity to tackle complex, ambiguous problems that touch every part of the firm's data ecosystem and to build ML solutions that actually make decisions. Job Responsibilities: Architect and develop scalable Python-based systems that support ML-driven risk classification, tagging, and approval triage Integrate ML models into microservices and APIs for use within AI Judge workflows Lead engineering design reviews, establish coding standards, and ensure system robustness and security Build and maintain feature pipelines and model-serving infrastructure using cloud-native tools Work closely with ML scientists, data engineers, and product managers to align on requirements and delivery timelines Drive engineering quality, CI/CD integration, observability, and unit testing for AI-enabled software components Mentor junior engineers and uphold engineering excellence across the team Required Qualifications, Capabilities, and Skills: Master's degree in computer science, Software Engineering, or related field 6+ years of experience as a backend or AI/ML software engineer Proficiency in Python with deep experience in building distributed and containerized services (e.g., Flask/FastAPI, Docker, Kubernetes) Strong understanding of ML deployment workflows, feature engineering, and serving architectures Experience building and deploying APIs and ML inference services in production Familiarity with ML model management, versioning, and performance monitoring Strong engineering fundamentals: data structures, system design, testing, and performance optimization Excellent communication and collaboration skills across technical and non-technical teams Preferred Qualifications, Capabilities, and Skills: Experience with AWS cloud stack (S3, SageMaker, Lambda, ECS, etc.) Experience working with structured data, tabular models, and metadata-driven platforms Experience with regulated data systems, enterprise controls, or secure data processing workflows Contributions to open-source ML or backend tooling frameworks About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Jul 16, 2025
Full time
Job Description Join the Chief Data & Analytics Office (CDAO) at JPMorgan Chase and be part of a team that accelerates the firm's data and analytics journey. We focus on ensuring data quality and security while leveraging insights to promote decision-making and support commercial goals through AI and machine learning. As an AI ML Lead Software Engineer within the Chief Data & Analytics Office, you will become part of a mission to modernize compliance through scalable and explainable AI. We are building a system that answers the question: "Can I use this data?", not with guesswork, but with prediction/classification, logic, proof, and intelligent automation. Our work sits at the intersection of applied machine learning, AI reasoning systems, and data governance. We are designing the triage layer of an intelligent decision engine that combines ML-driven classification, LLM-assisted parsing, and formal logic-based verification. This is an opportunity to tackle complex, ambiguous problems that touch every part of the firm's data ecosystem and to build ML solutions that actually make decisions. Job Responsibilities: Architect and develop scalable Python-based systems that support ML-driven risk classification, tagging, and approval triage Integrate ML models into microservices and APIs for use within AI Judge workflows Lead engineering design reviews, establish coding standards, and ensure system robustness and security Build and maintain feature pipelines and model-serving infrastructure using cloud-native tools Work closely with ML scientists, data engineers, and product managers to align on requirements and delivery timelines Drive engineering quality, CI/CD integration, observability, and unit testing for AI-enabled software components Mentor junior engineers and uphold engineering excellence across the team Required Qualifications, Capabilities, and Skills: Master's degree in computer science, Software Engineering, or related field 6+ years of experience as a backend or AI/ML software engineer Proficiency in Python with deep experience in building distributed and containerized services (e.g., Flask/FastAPI, Docker, Kubernetes) Strong understanding of ML deployment workflows, feature engineering, and serving architectures Experience building and deploying APIs and ML inference services in production Familiarity with ML model management, versioning, and performance monitoring Strong engineering fundamentals: data structures, system design, testing, and performance optimization Excellent communication and collaboration skills across technical and non-technical teams Preferred Qualifications, Capabilities, and Skills: Experience with AWS cloud stack (S3, SageMaker, Lambda, ECS, etc.) Experience working with structured data, tabular models, and metadata-driven platforms Experience with regulated data systems, enterprise controls, or secure data processing workflows Contributions to open-source ML or backend tooling frameworks About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team Job ID: AWS EMEA SARL (UK Branch) Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - 2+ years of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals PREFERRED QUALIFICATIONS - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: April 2, 2025 (Updated 1 day ago) Posted: March 3, 2025 (Updated 4 days ago) Posted: April 3, 2024 (Updated 6 days ago) Posted: April 28, 2025 (Updated 8 days ago) Posted: April 22, 2025 (Updated 14 days ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Jul 16, 2025
Full time
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team Job ID: AWS EMEA SARL (UK Branch) Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds' leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We're looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience Provide customer and market feedback to product and engineering teams to help define product direction Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of hands on experience with Python to build, train, and evaluate models - 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - 2+ years of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies - Experience in patents or publications at peer-reviewed conferences or journals PREFERRED QUALIFICATIONS - Experience working in a startup or with startup customers - Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches - Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation - Experience with optimization of models on GPUs, Amazon Silicon, or TPUs, also experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools - Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Posted: April 2, 2025 (Updated 1 day ago) Posted: March 3, 2025 (Updated 4 days ago) Posted: April 3, 2024 (Updated 6 days ago) Posted: April 28, 2025 (Updated 8 days ago) Posted: April 22, 2025 (Updated 14 days ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Cambridge, Gatwick, Milton Keynes, Reading Business Line Enabling Functions Job Type Permanent / FTC Date published 08-Jul-2025 19636 Connect to your Industry Are you passionate about data science and AI? Do you want to apply your skills and knowledge to help shape the future of Deloitte? If so, we have an exciting opportunity for you to join our Enabling Functions team as an AI Engineer & Data Scientist. You be part of an exciting innovative team that delivers cutting edge GenAI solutions. As an AI Engineer & Data Scientist, you will work on innovative projects that leverage data and AI to enhance our internal capabilities and deliver value to our employees. You will collaborate with experts from across the firm, using cutting-edge tools and technologies to solve complex business problems. You will also have the opportunity to develop your career and learn new skills in a supportive and inclusive environment. You will be reporting to the Head of AI-CoE. Connect to your career at Deloitte Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more. What brings us all together at Deloitte?It'show we approach the thousands of decisions we make everyday. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, whereverwe arein the world, we lead the way , serve with integrity , take care of each other , fosterinclusion , and collaborate for measurable impact . These five shared values lead every decision wemake and action we take, guiding us to deliver impact how and where it mattersmost . Connect to your opportunity As an AI Engineer & Data Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use of AI and adherence to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as Python and familiar with data science and AI libraries and frameworks. Expert in implementing Agentic AI solutions, MCP protocols and integrating with GenAI based applications. Experience in working with cloud platforms and services, such as Azure, AWS and GCP. Excellent communication, collaboration, and stakeholder management skills. Certifications or accreditations in data science, AI, or cloud technologies. Expertise in prompt engineering. Prior experience with ethical AI practices and data privacy is highly desirable. Connect to your business -Enabling Functions Collaboration is central to everything we do at Deloitte. From IT to HR, marketing and more, our teams help to support the wider business in everything they do. Bringing your individual skills and specialist knowledge, you can make a far-reaching impact. Come join us. Central business services We deliver world-class business support services for our people, our clients and our firm. From HR services, technology and digital support and pensions to facilities management, and more - together we are a true enabler for better business. Personal independence Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests and employment relationships). This can mean that you and your "Immediate Family Members" are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further detail as you progress through the recruitment process or you can contact the Independence team upon request. Connect with your colleagues "Good HR (Human Resource) is about far more than bringing the right new talent into the business. In addition to leading the way in recruitment, we are the ones making sure that flexibility and inclusivity are more than just soundbites." "The support that Deloitte offers is great, and the work is always interesting and motivating." "The amount of investment in me in terms of training and development has been incredible - it has undoubtedly helped me to progress my career." -Jim, Enabling Functions Our hybrid working policy You'll be based in Cambridge, Gatwick, Milton Keynes or Reading with hybrid working. At Deloitte we understand the importance of balancing your career alongside your home life.That's why we'll support you to work flexibly through our hybrid working policy. Depending on the requirements of your role, you'll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You'll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritiseyour wellbeing. Please check with your recruiter for the specific working requirements that may apply for your role. Our commitment to you Making an impact is more than just what we do: it's why we're here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before. We want you. The true you. Your own strengths, perspective and personality. So we're nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we'll take your wellbeing seriously, too. Because it's only when you're comfortable and at your best that you can make the kind of impact you, and we, live for. Your expertise is our capability, so we'll make sure it never stops growing. Whether it's from the complex work you do, or the people you collaborate with, you'll learn every day. Through world-class development, you'll gain invaluable technical and personal skills. Whatever your level, you'll learn how to lead. Connect to your next step A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you'll experience a purpose you can believe in and an impact you can see. You'll be free to bring your true self to work every day. And you'll never stop growing, whatever your level . Discover more reasons to connect with us, our people and purpose-driven culture at deloitte.co.uk/careers WPFULL SLICSS LOCCAM LOCGAT LOOCMIL LOCREA
Jul 10, 2025
Full time
Cambridge, Gatwick, Milton Keynes, Reading Business Line Enabling Functions Job Type Permanent / FTC Date published 08-Jul-2025 19636 Connect to your Industry Are you passionate about data science and AI? Do you want to apply your skills and knowledge to help shape the future of Deloitte? If so, we have an exciting opportunity for you to join our Enabling Functions team as an AI Engineer & Data Scientist. You be part of an exciting innovative team that delivers cutting edge GenAI solutions. As an AI Engineer & Data Scientist, you will work on innovative projects that leverage data and AI to enhance our internal capabilities and deliver value to our employees. You will collaborate with experts from across the firm, using cutting-edge tools and technologies to solve complex business problems. You will also have the opportunity to develop your career and learn new skills in a supportive and inclusive environment. You will be reporting to the Head of AI-CoE. Connect to your career at Deloitte Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more. What brings us all together at Deloitte?It'show we approach the thousands of decisions we make everyday. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, whereverwe arein the world, we lead the way , serve with integrity , take care of each other , fosterinclusion , and collaborate for measurable impact . These five shared values lead every decision wemake and action we take, guiding us to deliver impact how and where it mattersmost . Connect to your opportunity As an AI Engineer & Data Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use of AI and adherence to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as Python and familiar with data science and AI libraries and frameworks. Expert in implementing Agentic AI solutions, MCP protocols and integrating with GenAI based applications. Experience in working with cloud platforms and services, such as Azure, AWS and GCP. Excellent communication, collaboration, and stakeholder management skills. Certifications or accreditations in data science, AI, or cloud technologies. Expertise in prompt engineering. Prior experience with ethical AI practices and data privacy is highly desirable. Connect to your business -Enabling Functions Collaboration is central to everything we do at Deloitte. From IT to HR, marketing and more, our teams help to support the wider business in everything they do. Bringing your individual skills and specialist knowledge, you can make a far-reaching impact. Come join us. Central business services We deliver world-class business support services for our people, our clients and our firm. From HR services, technology and digital support and pensions to facilities management, and more - together we are a true enabler for better business. Personal independence Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests and employment relationships). This can mean that you and your "Immediate Family Members" are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further detail as you progress through the recruitment process or you can contact the Independence team upon request. Connect with your colleagues "Good HR (Human Resource) is about far more than bringing the right new talent into the business. In addition to leading the way in recruitment, we are the ones making sure that flexibility and inclusivity are more than just soundbites." "The support that Deloitte offers is great, and the work is always interesting and motivating." "The amount of investment in me in terms of training and development has been incredible - it has undoubtedly helped me to progress my career." -Jim, Enabling Functions Our hybrid working policy You'll be based in Cambridge, Gatwick, Milton Keynes or Reading with hybrid working. At Deloitte we understand the importance of balancing your career alongside your home life.That's why we'll support you to work flexibly through our hybrid working policy. Depending on the requirements of your role, you'll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You'll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritiseyour wellbeing. Please check with your recruiter for the specific working requirements that may apply for your role. Our commitment to you Making an impact is more than just what we do: it's why we're here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before. We want you. The true you. Your own strengths, perspective and personality. So we're nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we'll take your wellbeing seriously, too. Because it's only when you're comfortable and at your best that you can make the kind of impact you, and we, live for. Your expertise is our capability, so we'll make sure it never stops growing. Whether it's from the complex work you do, or the people you collaborate with, you'll learn every day. Through world-class development, you'll gain invaluable technical and personal skills. Whatever your level, you'll learn how to lead. Connect to your next step A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you'll experience a purpose you can believe in and an impact you can see. You'll be free to bring your true self to work every day. And you'll never stop growing, whatever your level . Discover more reasons to connect with us, our people and purpose-driven culture at deloitte.co.uk/careers WPFULL SLICSS LOCCAM LOCGAT LOOCMIL LOCREA
Cambridge, Gatwick, Milton Keynes, Reading Business Line Enabling Functions Job Type Permanent / FTC Date published 08-Jul-2025 19636 Connect to your Industry Are you passionate about data science and AI? Do you want to apply your skills and knowledge to help shape the future of Deloitte? If so, we have an exciting opportunity for you to join our Enabling Functions team as an AI Engineer & Data Scientist. You be part of an exciting innovative team that delivers cutting edge GenAI solutions. As an AI Engineer & Data Scientist, you will work on innovative projects that leverage data and AI to enhance our internal capabilities and deliver value to our employees. You will collaborate with experts from across the firm, using cutting-edge tools and technologies to solve complex business problems. You will also have the opportunity to develop your career and learn new skills in a supportive and inclusive environment. You will be reporting to the Head of AI-CoE. Connect to your career at Deloitte Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more. What brings us all together at Deloitte?It'show we approach the thousands of decisions we make everyday. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, whereverwe arein the world, we lead the way , serve with integrity , take care of each other , fosterinclusion , and collaborate for measurable impact . These five shared values lead every decision wemake and action we take, guiding us to deliver impact how and where it mattersmost . Connect to your opportunity As an AI Engineer & Data Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use of AI and adherence to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as Python and familiar with data science and AI libraries and frameworks. Expert in implementing Agentic AI solutions, MCP protocols and integrating with GenAI based applications. Experience in working with cloud platforms and services, such as Azure, AWS and GCP. Excellent communication, collaboration, and stakeholder management skills. Certifications or accreditations in data science, AI, or cloud technologies. Expertise in prompt engineering. Prior experience with ethical AI practices and data privacy is highly desirable. Connect to your business -Enabling Functions Collaboration is central to everything we do at Deloitte. From IT to HR, marketing and more, our teams help to support the wider business in everything they do. Bringing your individual skills and specialist knowledge, you can make a far-reaching impact. Come join us. Central business services We deliver world-class business support services for our people, our clients and our firm. From HR services, technology and digital support and pensions to facilities management, and more - together we are a true enabler for better business. Personal independence Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests and employment relationships). This can mean that you and your "Immediate Family Members" are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further detail as you progress through the recruitment process or you can contact the Independence team upon request. Connect with your colleagues "Good HR (Human Resource) is about far more than bringing the right new talent into the business. In addition to leading the way in recruitment, we are the ones making sure that flexibility and inclusivity are more than just soundbites." "The support that Deloitte offers is great, and the work is always interesting and motivating." "The amount of investment in me in terms of training and development has been incredible - it has undoubtedly helped me to progress my career." -Jim, Enabling Functions Our hybrid working policy You'll be based in Cambridge, Gatwick, Milton Keynes or Reading with hybrid working. At Deloitte we understand the importance of balancing your career alongside your home life.That's why we'll support you to work flexibly through our hybrid working policy. Depending on the requirements of your role, you'll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You'll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritiseyour wellbeing. Please check with your recruiter for the specific working requirements that may apply for your role. Our commitment to you Making an impact is more than just what we do: it's why we're here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before. We want you. The true you. Your own strengths, perspective and personality. So we're nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we'll take your wellbeing seriously, too. Because it's only when you're comfortable and at your best that you can make the kind of impact you, and we, live for. Your expertise is our capability, so we'll make sure it never stops growing. Whether it's from the complex work you do, or the people you collaborate with, you'll learn every day. Through world-class development, you'll gain invaluable technical and personal skills. Whatever your level, you'll learn how to lead. Connect to your next step A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you'll experience a purpose you can believe in and an impact you can see. You'll be free to bring your true self to work every day. And you'll never stop growing, whatever your level . Discover more reasons to connect with us, our people and purpose-driven culture at deloitte.co.uk/careers WPFULL SLICSS LOCCAM LOCGAT LOOCMIL LOCREA
Jul 10, 2025
Full time
Cambridge, Gatwick, Milton Keynes, Reading Business Line Enabling Functions Job Type Permanent / FTC Date published 08-Jul-2025 19636 Connect to your Industry Are you passionate about data science and AI? Do you want to apply your skills and knowledge to help shape the future of Deloitte? If so, we have an exciting opportunity for you to join our Enabling Functions team as an AI Engineer & Data Scientist. You be part of an exciting innovative team that delivers cutting edge GenAI solutions. As an AI Engineer & Data Scientist, you will work on innovative projects that leverage data and AI to enhance our internal capabilities and deliver value to our employees. You will collaborate with experts from across the firm, using cutting-edge tools and technologies to solve complex business problems. You will also have the opportunity to develop your career and learn new skills in a supportive and inclusive environment. You will be reporting to the Head of AI-CoE. Connect to your career at Deloitte Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more. What brings us all together at Deloitte?It'show we approach the thousands of decisions we make everyday. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, whereverwe arein the world, we lead the way , serve with integrity , take care of each other , fosterinclusion , and collaborate for measurable impact . These five shared values lead every decision wemake and action we take, guiding us to deliver impact how and where it mattersmost . Connect to your opportunity As an AI Engineer & Data Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use of AI and adherence to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as Python and familiar with data science and AI libraries and frameworks. Expert in implementing Agentic AI solutions, MCP protocols and integrating with GenAI based applications. Experience in working with cloud platforms and services, such as Azure, AWS and GCP. Excellent communication, collaboration, and stakeholder management skills. Certifications or accreditations in data science, AI, or cloud technologies. Expertise in prompt engineering. Prior experience with ethical AI practices and data privacy is highly desirable. Connect to your business -Enabling Functions Collaboration is central to everything we do at Deloitte. From IT to HR, marketing and more, our teams help to support the wider business in everything they do. Bringing your individual skills and specialist knowledge, you can make a far-reaching impact. Come join us. Central business services We deliver world-class business support services for our people, our clients and our firm. From HR services, technology and digital support and pensions to facilities management, and more - together we are a true enabler for better business. Personal independence Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests and employment relationships). This can mean that you and your "Immediate Family Members" are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further detail as you progress through the recruitment process or you can contact the Independence team upon request. Connect with your colleagues "Good HR (Human Resource) is about far more than bringing the right new talent into the business. In addition to leading the way in recruitment, we are the ones making sure that flexibility and inclusivity are more than just soundbites." "The support that Deloitte offers is great, and the work is always interesting and motivating." "The amount of investment in me in terms of training and development has been incredible - it has undoubtedly helped me to progress my career." -Jim, Enabling Functions Our hybrid working policy You'll be based in Cambridge, Gatwick, Milton Keynes or Reading with hybrid working. At Deloitte we understand the importance of balancing your career alongside your home life.That's why we'll support you to work flexibly through our hybrid working policy. Depending on the requirements of your role, you'll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You'll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritiseyour wellbeing. Please check with your recruiter for the specific working requirements that may apply for your role. Our commitment to you Making an impact is more than just what we do: it's why we're here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before. We want you. The true you. Your own strengths, perspective and personality. So we're nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we'll take your wellbeing seriously, too. Because it's only when you're comfortable and at your best that you can make the kind of impact you, and we, live for. Your expertise is our capability, so we'll make sure it never stops growing. Whether it's from the complex work you do, or the people you collaborate with, you'll learn every day. Through world-class development, you'll gain invaluable technical and personal skills. Whatever your level, you'll learn how to lead. Connect to your next step A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you'll experience a purpose you can believe in and an impact you can see. You'll be free to bring your true self to work every day. And you'll never stop growing, whatever your level . Discover more reasons to connect with us, our people and purpose-driven culture at deloitte.co.uk/careers WPFULL SLICSS LOCCAM LOCGAT LOOCMIL LOCREA
About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on About The Job Mistral AI is seeking an Applied Scientist to drive innovative research and facilitate the adoption of its products among customers, collaborating with them to address complex technical challenges. The Applied Scientist will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations. In this role, you'll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalizing our research in production settings. What you will do • Work in collaboration with our researchers, other AI engineers, and product engineers on our most complex customer projects involving co-training, fine-tuning, and various special projects. • Evaluate and improve the performance of our models on a variety of use cases (e.g., reasoning, code, RAG, tool use, agents) and across modalities (text, image, speech). • Develop complex use cases with our customers, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces. • Maintain a suite of technical packages, including scientific tooling design to help customers. About you • You are fluent in English • You hold a PhD / master in AI / data science. • You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products • You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases • You have deep understanding of concepts and algorithms underlying machine learning and LLMs • You're experienced with building and deploying LLMs or NLP applications • You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. • You have strong technical coding skills in Python • You have experience with deep learning with Pytorch • You have experience with agents framework such as Langchain, vector DBs • You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: • Contributed to open-source projects in particular in the space of LLMs • Hands-on experience with Generative AI (e.g., experience with transformer-based models) and a broad knowledge of the field of AI • Publication record in AI or a related field • Strong interest in pre-training fine-tuning and using language models for applications • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager Benefits We have local offices in Paris, London, Marseille and Singapore. France Competitive cash salary and equity Food : Daily lunch vouchers Sport : Monthly contribution to a Gympass subscription Transportation : Monthly contribution to a mobility pass ️ Health : Full health insurance for you and your family Parental : Generous parental leave policy Visa sponsorship UK Competitive cash salary and equity Insurance Transportation: Reimburse office parking charges, or 90GBP/month for public transport Sport: 90GBP/month reimbursement for gym membership Meal voucher: £200 monthly allowance for its meals Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)
Jul 09, 2025
Full time
About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on About The Job Mistral AI is seeking an Applied Scientist to drive innovative research and facilitate the adoption of its products among customers, collaborating with them to address complex technical challenges. The Applied Scientist will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations. In this role, you'll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalizing our research in production settings. What you will do • Work in collaboration with our researchers, other AI engineers, and product engineers on our most complex customer projects involving co-training, fine-tuning, and various special projects. • Evaluate and improve the performance of our models on a variety of use cases (e.g., reasoning, code, RAG, tool use, agents) and across modalities (text, image, speech). • Develop complex use cases with our customers, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces. • Maintain a suite of technical packages, including scientific tooling design to help customers. About you • You are fluent in English • You hold a PhD / master in AI / data science. • You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products • You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases • You have deep understanding of concepts and algorithms underlying machine learning and LLMs • You're experienced with building and deploying LLMs or NLP applications • You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. • You have strong technical coding skills in Python • You have experience with deep learning with Pytorch • You have experience with agents framework such as Langchain, vector DBs • You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: • Contributed to open-source projects in particular in the space of LLMs • Hands-on experience with Generative AI (e.g., experience with transformer-based models) and a broad knowledge of the field of AI • Publication record in AI or a related field • Strong interest in pre-training fine-tuning and using language models for applications • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager Benefits We have local offices in Paris, London, Marseille and Singapore. France Competitive cash salary and equity Food : Daily lunch vouchers Sport : Monthly contribution to a Gympass subscription Transportation : Monthly contribution to a mobility pass ️ Health : Full health insurance for you and your family Parental : Generous parental leave policy Visa sponsorship UK Competitive cash salary and equity Insurance Transportation: Reimburse office parking charges, or 90GBP/month for public transport Sport: 90GBP/month reimbursement for gym membership Meal voucher: £200 monthly allowance for its meals Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)
Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science. Our Physical Sciences effort is developing a novel AI and data-driven approach to materials discovery and development to accelerate the transition to a sustainable economy. At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you'd love to work in, even if you only have some of the experience listed below, please apply. The Role We are seeking a Team Lead for Applied Machine Learning (ML) in Physical Sciences to oversee and guide a team of engineers and researchers working on cutting-edge AI models for materials, chemistry, and physics. The Team Lead will drive the development of AI/ML models for materials discovery, foster collaboration across teams, and provide strategic direction for AI integration in the materials science domain. Key Responsibilities: Lead and mentor a cross-disciplinary team: Supervise and support a group of ML engineers and scientists, guiding them in applying ML techniques to materials composition, structure, and performance. Develop and deploy advanced ML models: Oversee the creation, fine-tuning, and deployment of deep learning models, with a focus on materials discovery, synthesis, and performance prediction. Drive innovation in physics-informed AI: Lead the development of physics-based learning architectures, integrating conservation laws, symmetries, and other scientific principles into AI models. Integrate AI tools with lab workflows: Collaborate closely with experimental teams to design AI-driven methods for lab orchestration, experimental assay design, and optimization of synthesis processes. Oversee computational projects: Ensure team members are successfully implementing deep learning architectures for representation learning, generative AI, and quantitative reasoning tools (e.g., LLMs). Strategize on AI-driven discovery: Shape the team's long-term goals for applying AI to optimize materials discovery, including digital platforms that continually fine-tune models as new data emerges. Communicate findings and strategies: Represent the team's work to stakeholders through presentations, reports, and technical documentation, ensuring clear communication of complex AI-driven insights. Stay at the forefront of AI and materials science: Keep the team up to date with the latest advancements in AI, ML, and materials research, integrating cutting-edge techniques into the team's approach. Must-Have Qualifications: Proven experience in leading teams in AI/ML applied to physical sciences, particularly in materials science, chemistry, or physics. Expertise in training, deploying, and fine-tuning deep learning models with applications in materials composition and performance prediction. Strong background in developing physics-informed machine learning models, including conservation laws, symmetry, PINNs, or neural ODEs. Proficiency with PyTorch and experience managing multi-GPU training environments. Demonstrated track record of publishing scientific papers or contributing to public codebases in the areas of AI and materials science. Proficiency in Python and the data science ecosystem (NumPy, SciPy, Pandas), along with data visualization tools. PhD in Computer Science, Applied Mathematics, Materials Science, or a related field, with a strong focus on machine learning. Excellent communication and leadership skills to manage a diverse team and convey technical findings to stakeholders. Preferred Qualifications: Experience with cloud computing services (e.g., AWS) to optimize training and evaluation processes. Familiarity with integrating machine learning into experimental workflows in materials science or chemistry. Knowledge of high-throughput experimental platforms for accelerated discovery. Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Feb 18, 2025
Full time
Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science. Our Physical Sciences effort is developing a novel AI and data-driven approach to materials discovery and development to accelerate the transition to a sustainable economy. At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you'd love to work in, even if you only have some of the experience listed below, please apply. The Role We are seeking a Team Lead for Applied Machine Learning (ML) in Physical Sciences to oversee and guide a team of engineers and researchers working on cutting-edge AI models for materials, chemistry, and physics. The Team Lead will drive the development of AI/ML models for materials discovery, foster collaboration across teams, and provide strategic direction for AI integration in the materials science domain. Key Responsibilities: Lead and mentor a cross-disciplinary team: Supervise and support a group of ML engineers and scientists, guiding them in applying ML techniques to materials composition, structure, and performance. Develop and deploy advanced ML models: Oversee the creation, fine-tuning, and deployment of deep learning models, with a focus on materials discovery, synthesis, and performance prediction. Drive innovation in physics-informed AI: Lead the development of physics-based learning architectures, integrating conservation laws, symmetries, and other scientific principles into AI models. Integrate AI tools with lab workflows: Collaborate closely with experimental teams to design AI-driven methods for lab orchestration, experimental assay design, and optimization of synthesis processes. Oversee computational projects: Ensure team members are successfully implementing deep learning architectures for representation learning, generative AI, and quantitative reasoning tools (e.g., LLMs). Strategize on AI-driven discovery: Shape the team's long-term goals for applying AI to optimize materials discovery, including digital platforms that continually fine-tune models as new data emerges. Communicate findings and strategies: Represent the team's work to stakeholders through presentations, reports, and technical documentation, ensuring clear communication of complex AI-driven insights. Stay at the forefront of AI and materials science: Keep the team up to date with the latest advancements in AI, ML, and materials research, integrating cutting-edge techniques into the team's approach. Must-Have Qualifications: Proven experience in leading teams in AI/ML applied to physical sciences, particularly in materials science, chemistry, or physics. Expertise in training, deploying, and fine-tuning deep learning models with applications in materials composition and performance prediction. Strong background in developing physics-informed machine learning models, including conservation laws, symmetry, PINNs, or neural ODEs. Proficiency with PyTorch and experience managing multi-GPU training environments. Demonstrated track record of publishing scientific papers or contributing to public codebases in the areas of AI and materials science. Proficiency in Python and the data science ecosystem (NumPy, SciPy, Pandas), along with data visualization tools. PhD in Computer Science, Applied Mathematics, Materials Science, or a related field, with a strong focus on machine learning. Excellent communication and leadership skills to manage a diverse team and convey technical findings to stakeholders. Preferred Qualifications: Experience with cloud computing services (e.g., AWS) to optimize training and evaluation processes. Familiarity with integrating machine learning into experimental workflows in materials science or chemistry. Knowledge of high-throughput experimental platforms for accelerated discovery. Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
AI Engineer x3 days a week in office Xcede are delighted to be working with a brilliant FTSE 250 Financial organisation beloved by nearly half a million users. The company works on a truly global scale and processes millions of transactions & decisions every day. Data is at the heart of the business, and in addition to pre-existing Data Scientists & Machine Learning Engineers, the organisation is looking to continue scaling their AI departments with a new AI Engineer. The unit is responsible for building innovative AI (& specifically LLM led) tools for both internal stakeholders across various departments and their many customers. Responsibilities Develop and deploy predictive models and algorithms for commercial projects with a particular focus on LLMs and RAGs. Collaborate with cross-functional commercial and business teams to understand business requirements and identify opportunities for deploying statistical models. Build production-level Machine Learning models and be hands-on in deployment. Evaluate and select appropriate machine learning techniques and algorithms for solving commercial challenges. Requirements Several years of commercial experience in a Data Science role building statistical & machine learning models. Experience in building and deploying machine learning models in production. Excellent proficiency in Python. Particular experience in NLP, LLMs, and RAGs is highly prized given the focus on these projects. Deep understanding of model fine-tuning, evaluation metrics, and model deployment strategies in production environments. CI/CD & MLOps experience is valued. Experience implementing LLM Guardrails would be highly valued given the type of data involved. If this role interests you and you would like to learn more, please apply here or contact us via (feel free to include a CV for review).
Feb 17, 2025
Full time
AI Engineer x3 days a week in office Xcede are delighted to be working with a brilliant FTSE 250 Financial organisation beloved by nearly half a million users. The company works on a truly global scale and processes millions of transactions & decisions every day. Data is at the heart of the business, and in addition to pre-existing Data Scientists & Machine Learning Engineers, the organisation is looking to continue scaling their AI departments with a new AI Engineer. The unit is responsible for building innovative AI (& specifically LLM led) tools for both internal stakeholders across various departments and their many customers. Responsibilities Develop and deploy predictive models and algorithms for commercial projects with a particular focus on LLMs and RAGs. Collaborate with cross-functional commercial and business teams to understand business requirements and identify opportunities for deploying statistical models. Build production-level Machine Learning models and be hands-on in deployment. Evaluate and select appropriate machine learning techniques and algorithms for solving commercial challenges. Requirements Several years of commercial experience in a Data Science role building statistical & machine learning models. Experience in building and deploying machine learning models in production. Excellent proficiency in Python. Particular experience in NLP, LLMs, and RAGs is highly prized given the focus on these projects. Deep understanding of model fine-tuning, evaluation metrics, and model deployment strategies in production environments. CI/CD & MLOps experience is valued. Experience implementing LLM Guardrails would be highly valued given the type of data involved. If this role interests you and you would like to learn more, please apply here or contact us via (feel free to include a CV for review).
Time left to apply End Date: March 31, 2025 (30+ days left to apply) Job requisition id R26624 At FactSet, we're working to be the best financial data provider. We need highly motivated, talented individuals empowered to find answers through creative technology to get there. As a Software Engineer in Data Solutions Engineering, you will be part of our Digital Transformation, a mission to automate our data acquisition, quality assurance, content creation, and analytics in a scalable cloud environment. With the guidance of financial experts, you will leverage these large data sets to improve the quality and extend the scope of FactSet's existing and next-generation products. You will be working on private market data, which are heterogeneous and voluminous datasets. With the right tools and problem-solving, we want to automate data collection at scale and infer information. The end goals are company classification, tag extraction, relationship mapping, and company valuation. There is huge potential for machine learning, analytics, and NLP. Your responsibilities: Build and scale an automatic data pipeline Ingest and analyze various data sources to drive innovation in content creation. Automate the acquisition, relevance scoring, and storage of incoming sources. Develop processes for data mining, data concordance, and data production. Explore and evaluate new data technologies to build a scalable, cloud-oriented data platform. Optimize data retrieval and develop dashboards and other visualizations for financial experts. Participate in different projects as a data scientist and data engineer Deliver clean, well-tested code that's reliable, maintainable, and scalable Build predictive models and communicate results with stakeholders Deploy working solutions Develop dashboards and other visualizations for financial experts. Develop processes for data collection, quality assessment, and quality control. Keep up to date / share your passions Stay up to date with state-of-the-art approaches and technological advancement Share your passion for science, ML, and technology Who are you? You have BS or MS in Computer Science or Mathematics related field. You have 3+ years of experience as a Software Engineer or Data Scientist. You have a successful history of writing and releasing production-grade code in an enterprise environment. You are a team player and adept at learning new technologies and client workflows You have experience working with Agile methodology. You have strong analytical skills You can communicate about complex subjects to non-technical stakeholders You are familiar with Terraform, Python , Pandas , and NumPy It is great if you have: Experience with Neural Networks / Deep Learning. Experience with information extraction, parsing, and segmentation. Experience with machine learning frameworks (sklearn ) and ML workflow. Experience with NLP libraries and text preprocessing (nltk, SpaCy, language models, ). Experience with cloud environments: AWS, Azure. Experience with business intelligence tools like Tableau or PowerBI. Experience working with LLMs. Experience working with AWS Services like EC2, RDS(Postgres), SQS, Sagemaker, MLflow, S3, API gateway, ECS. Experience in UI frameworks like VueJS is a plus. About Us FactSet creates flexible, open data and software solutions for tens of thousands of investment professionals around the world, providing instant access to financial data and analytics that investors use to make crucial decisions. Join a team of highly motivated, talented individuals who are empowered to find answers through creative technology.
Feb 17, 2025
Full time
Time left to apply End Date: March 31, 2025 (30+ days left to apply) Job requisition id R26624 At FactSet, we're working to be the best financial data provider. We need highly motivated, talented individuals empowered to find answers through creative technology to get there. As a Software Engineer in Data Solutions Engineering, you will be part of our Digital Transformation, a mission to automate our data acquisition, quality assurance, content creation, and analytics in a scalable cloud environment. With the guidance of financial experts, you will leverage these large data sets to improve the quality and extend the scope of FactSet's existing and next-generation products. You will be working on private market data, which are heterogeneous and voluminous datasets. With the right tools and problem-solving, we want to automate data collection at scale and infer information. The end goals are company classification, tag extraction, relationship mapping, and company valuation. There is huge potential for machine learning, analytics, and NLP. Your responsibilities: Build and scale an automatic data pipeline Ingest and analyze various data sources to drive innovation in content creation. Automate the acquisition, relevance scoring, and storage of incoming sources. Develop processes for data mining, data concordance, and data production. Explore and evaluate new data technologies to build a scalable, cloud-oriented data platform. Optimize data retrieval and develop dashboards and other visualizations for financial experts. Participate in different projects as a data scientist and data engineer Deliver clean, well-tested code that's reliable, maintainable, and scalable Build predictive models and communicate results with stakeholders Deploy working solutions Develop dashboards and other visualizations for financial experts. Develop processes for data collection, quality assessment, and quality control. Keep up to date / share your passions Stay up to date with state-of-the-art approaches and technological advancement Share your passion for science, ML, and technology Who are you? You have BS or MS in Computer Science or Mathematics related field. You have 3+ years of experience as a Software Engineer or Data Scientist. You have a successful history of writing and releasing production-grade code in an enterprise environment. You are a team player and adept at learning new technologies and client workflows You have experience working with Agile methodology. You have strong analytical skills You can communicate about complex subjects to non-technical stakeholders You are familiar with Terraform, Python , Pandas , and NumPy It is great if you have: Experience with Neural Networks / Deep Learning. Experience with information extraction, parsing, and segmentation. Experience with machine learning frameworks (sklearn ) and ML workflow. Experience with NLP libraries and text preprocessing (nltk, SpaCy, language models, ). Experience with cloud environments: AWS, Azure. Experience with business intelligence tools like Tableau or PowerBI. Experience working with LLMs. Experience working with AWS Services like EC2, RDS(Postgres), SQS, Sagemaker, MLflow, S3, API gateway, ECS. Experience in UI frameworks like VueJS is a plus. About Us FactSet creates flexible, open data and software solutions for tens of thousands of investment professionals around the world, providing instant access to financial data and analytics that investors use to make crucial decisions. Join a team of highly motivated, talented individuals who are empowered to find answers through creative technology.
Senior Machine Learning Engineer page is loaded Senior Machine Learning Engineer Job Title Senior Machine Learning Engineer Job Description Here at UnderwriteMe, we are on a mission to make life insurance more widely accessible and ensure people and their loved ones are protected when the inevitable happens. We are doing this by reshaping the future of insurance through innovative and global technology products. As we work on solving complex problems that will change how lives are protected, we operate in a fast-paced, challenging environment. The type of people who work for us embrace and relish the challenge and in turn the sense of achievement in helping to solve these problems and making an impact on how lives are protected. We place a great emphasis on challenging the status quo and constantly striving to improve on what we do. We want to get to the point where we are leading the way in the software industry. Being owned by Pacific Life, we have the best of both worlds - the freedom to experiment like a start-up with the stability of our parent company. If you want to bring new ideas to the table and be part of a team working on innovative technology, come and join us. Job Description We are currently seeking an innovative Senior AI / Machine Learning Engineer to join UnderwriteMe within the Text Mining team. This role is pivotal in driving the creation of an innovative product set to disrupt the insurance market. We are looking for candidates with a proven track record in the design and deployment of LLMs for applications within the NLP space, as well as established experience collaborating with product managers, developers, and fellow data scientists within a product-led SaaS environment. What will you be doing? Working within a dynamic cross-functional team that operates based on OKRs (Objectives and Key Results), fostering collaboration among developers, QAs, data scientists, and data analysts, to consistently achieve tangible outcomes aligned with OKR targets. Employing your deep understanding of AI and staying current with industry trends, you will play a pivotal role in shaping project execution by contributing to the OKR formulation process, and directly working towards those. Crafting and refining Machine Learning models and algorithms to address complex product challenges. Devising and implementing innovative data analysis and data mining strategies, extracting valuable insights from diverse data sources. Harnessing the power of natural language processing (NLP) techniques to extract pertinent information from textual data. Formulating predictive models to anticipate future trends, enabling informed decision-making. Constructing automated ML workflows and integrating CI/CD practices to ensure seamless model deployment and recurrent refinement. Architecting, deploying, and overseeing APIs for effective model delivery, while also leveraging external APIs to enhance functionality. Establishing monitoring and logging systems to evaluate model performance, detect anomalies, and guarantee consistent model dependability and accessibility. Collaborating closely with DevOps and IT teams to orchestrate the smooth transition of ML models into production environments, upholding scalability and security standards. Technical Requirements Applied AI and NLP Expertise: Proven experience in applying AI techniques to solve real-world NLP problems, with a focus on delivering scalable, production-ready solutions. Hands-on expertise in fine-tuning pre-trained models such as BERT, GPT, or similar transformer-based architectures for domain-specific tasks in the NLP space. Experience in integrating Large Language Models (LLMs) into applications, with a focus on enabling structured responses, such as through APIs or with purpose-built LLMs. Knowledge of prompt engineering techniques, including designing effective prompts for different tasks, optimizing input/output formats, and leveraging techniques such as few-shot learning. Advanced Python Development Proficiency: Experience with OOP, and data-validation libraries such as Pydantic. Deep familiarity with Python and its ecosystem for AI/ML, including libraries like PyTorch, Hugging Face Transformers, and scikit-learn. Experience with data manipulation using libraries such as Pandas and NumPy, and familiarity with parallelization or asynchronous programming. Proficiency in Test-Driven Development (TDD) and an understanding of Python testing libraries such as Pytest. Cloud, CI/CD & MLOps Knowledge Experience taking models from experiments through to production deployments, with tools such as Docker, Kubernetes & serverless alternatives such as AWS Lambda. Familiarity with MLOps tools such as MLFlow, Kubeflow or Sagemaker. A strong knowledge of cloud platforms (ideally AWS) and their respective services for deploying robust, AI-heavy applications. Bonus Experience Experience with named entity recognition / recommendation systems. Knowledge of Gitlab's CI/CD (or Github Actions). Basic understanding of Java (ideally with Spring Boot). Experience working in a fast-paced, product-led environment. Experience working with data within the insurance / healthcare sector. Ideal Qualities Entrepreneurial Mindset The ideal candidate will possess a product-led, entrepreneurial approach to their work, constantly evaluating new technologies which may facilitate improvements to the product and directly relate back to OKRs. Experience in a fast-paced, start-up environment would be a bonus, with the ability to work both proactively and reactively. Exceptional Communicator / Collaborator The ability to confidently communicate technical concepts to both a technical and non-technical audience (both verbally & written), for example when discussing results, technical approaches, or resolutions to potential blockers. Extensive experience of collaboration with engineers, architects & product teams to enable robust solutions to solve real, well-defined problems. ML/AI Champion A deep appreciation for the possibilities of ML/AI on the application layer, and a strong desire to work on state-of-the-art applications where your ideas could directly translate to enormous business impact. Key Characteristics that we look for when interviewing and that help people thrive at UnderwriteMe: Entrepreneurial: Shows initiative and a proactive approach to identifying and seizing the right opportunities. Shows resilience in the face of challenges and maintains a bias for action. Curiosity: Exhibits a strong desire to learn and understand new concepts. Approaches problems with creativity and persistence, consistently seeking effective solutions. Technically Great: Possesses a deep understanding of relevant technical skills and knowledge applicable to their role. Applies technical expertise effectively to solve complex issues. Strategic Thinker: Understands the broader impact of their role and decisions. Effectively balances immediate actions with strategic planning to ensure alignment with medium-term and long-term organisational objectives. Impact Oriented: Driven by meaningful results, prioritising actions that deliver significant outcomes and contribute to team success. Motivated by value creation and business impact, not titles or status. Adaptability: Open to feedback and willing to learn from others. Shows a growth mindset and the ability to adapt and improve. About UnderwriteMe UnderwriteMe is an Insurtech software business and subsidiary of Pacific Life Re (PL Re), a global life and pensions reinsurance firm. We have a vision to help everyone purchase protection insurance by using data and disruptive technology to transform our partners and markets in order to make their underwriting processes as quick and efficient as possible. Our core products are: a best-in-market Underwriting Rules Engine which can be used to automate any structured data within the underwriting journey, and which is sold in the UK & Ireland, Asia-Pacific and North America the Protection Platform, an end-to-end quote and buy marketplace for Protection in the UK Working for UnderwriteMe Joining UnderwriteMe means being part of a technology company that is committed to bringing a fresh and dynamic approach to insurance. You'd be working with a team of highly technical experts made up of people with backgrounds in software, fintech, and insurance. Every person in our global team is valued for the unique qualities they bring to our business and we seek to build their expertise and support their individual ambitions at every step. Of course, we take our work seriously and we know our team can operate under great pressure. We work hard and thrive on achievement, but we also know how to have fun and relax too. We regularly host a range of team building days to strengthen our team's connection with each other and reflect on their successes. Providing employees with a healthy work-life balance is very important to our culture. We have a wide range of employee benefits and we host regular social activities and wellbeing initiatives. We are also committed to supporting our employee's involvement in their communities, by actively fundraising, hosting charity events . click apply for full job details
Feb 16, 2025
Full time
Senior Machine Learning Engineer page is loaded Senior Machine Learning Engineer Job Title Senior Machine Learning Engineer Job Description Here at UnderwriteMe, we are on a mission to make life insurance more widely accessible and ensure people and their loved ones are protected when the inevitable happens. We are doing this by reshaping the future of insurance through innovative and global technology products. As we work on solving complex problems that will change how lives are protected, we operate in a fast-paced, challenging environment. The type of people who work for us embrace and relish the challenge and in turn the sense of achievement in helping to solve these problems and making an impact on how lives are protected. We place a great emphasis on challenging the status quo and constantly striving to improve on what we do. We want to get to the point where we are leading the way in the software industry. Being owned by Pacific Life, we have the best of both worlds - the freedom to experiment like a start-up with the stability of our parent company. If you want to bring new ideas to the table and be part of a team working on innovative technology, come and join us. Job Description We are currently seeking an innovative Senior AI / Machine Learning Engineer to join UnderwriteMe within the Text Mining team. This role is pivotal in driving the creation of an innovative product set to disrupt the insurance market. We are looking for candidates with a proven track record in the design and deployment of LLMs for applications within the NLP space, as well as established experience collaborating with product managers, developers, and fellow data scientists within a product-led SaaS environment. What will you be doing? Working within a dynamic cross-functional team that operates based on OKRs (Objectives and Key Results), fostering collaboration among developers, QAs, data scientists, and data analysts, to consistently achieve tangible outcomes aligned with OKR targets. Employing your deep understanding of AI and staying current with industry trends, you will play a pivotal role in shaping project execution by contributing to the OKR formulation process, and directly working towards those. Crafting and refining Machine Learning models and algorithms to address complex product challenges. Devising and implementing innovative data analysis and data mining strategies, extracting valuable insights from diverse data sources. Harnessing the power of natural language processing (NLP) techniques to extract pertinent information from textual data. Formulating predictive models to anticipate future trends, enabling informed decision-making. Constructing automated ML workflows and integrating CI/CD practices to ensure seamless model deployment and recurrent refinement. Architecting, deploying, and overseeing APIs for effective model delivery, while also leveraging external APIs to enhance functionality. Establishing monitoring and logging systems to evaluate model performance, detect anomalies, and guarantee consistent model dependability and accessibility. Collaborating closely with DevOps and IT teams to orchestrate the smooth transition of ML models into production environments, upholding scalability and security standards. Technical Requirements Applied AI and NLP Expertise: Proven experience in applying AI techniques to solve real-world NLP problems, with a focus on delivering scalable, production-ready solutions. Hands-on expertise in fine-tuning pre-trained models such as BERT, GPT, or similar transformer-based architectures for domain-specific tasks in the NLP space. Experience in integrating Large Language Models (LLMs) into applications, with a focus on enabling structured responses, such as through APIs or with purpose-built LLMs. Knowledge of prompt engineering techniques, including designing effective prompts for different tasks, optimizing input/output formats, and leveraging techniques such as few-shot learning. Advanced Python Development Proficiency: Experience with OOP, and data-validation libraries such as Pydantic. Deep familiarity with Python and its ecosystem for AI/ML, including libraries like PyTorch, Hugging Face Transformers, and scikit-learn. Experience with data manipulation using libraries such as Pandas and NumPy, and familiarity with parallelization or asynchronous programming. Proficiency in Test-Driven Development (TDD) and an understanding of Python testing libraries such as Pytest. Cloud, CI/CD & MLOps Knowledge Experience taking models from experiments through to production deployments, with tools such as Docker, Kubernetes & serverless alternatives such as AWS Lambda. Familiarity with MLOps tools such as MLFlow, Kubeflow or Sagemaker. A strong knowledge of cloud platforms (ideally AWS) and their respective services for deploying robust, AI-heavy applications. Bonus Experience Experience with named entity recognition / recommendation systems. Knowledge of Gitlab's CI/CD (or Github Actions). Basic understanding of Java (ideally with Spring Boot). Experience working in a fast-paced, product-led environment. Experience working with data within the insurance / healthcare sector. Ideal Qualities Entrepreneurial Mindset The ideal candidate will possess a product-led, entrepreneurial approach to their work, constantly evaluating new technologies which may facilitate improvements to the product and directly relate back to OKRs. Experience in a fast-paced, start-up environment would be a bonus, with the ability to work both proactively and reactively. Exceptional Communicator / Collaborator The ability to confidently communicate technical concepts to both a technical and non-technical audience (both verbally & written), for example when discussing results, technical approaches, or resolutions to potential blockers. Extensive experience of collaboration with engineers, architects & product teams to enable robust solutions to solve real, well-defined problems. ML/AI Champion A deep appreciation for the possibilities of ML/AI on the application layer, and a strong desire to work on state-of-the-art applications where your ideas could directly translate to enormous business impact. Key Characteristics that we look for when interviewing and that help people thrive at UnderwriteMe: Entrepreneurial: Shows initiative and a proactive approach to identifying and seizing the right opportunities. Shows resilience in the face of challenges and maintains a bias for action. Curiosity: Exhibits a strong desire to learn and understand new concepts. Approaches problems with creativity and persistence, consistently seeking effective solutions. Technically Great: Possesses a deep understanding of relevant technical skills and knowledge applicable to their role. Applies technical expertise effectively to solve complex issues. Strategic Thinker: Understands the broader impact of their role and decisions. Effectively balances immediate actions with strategic planning to ensure alignment with medium-term and long-term organisational objectives. Impact Oriented: Driven by meaningful results, prioritising actions that deliver significant outcomes and contribute to team success. Motivated by value creation and business impact, not titles or status. Adaptability: Open to feedback and willing to learn from others. Shows a growth mindset and the ability to adapt and improve. About UnderwriteMe UnderwriteMe is an Insurtech software business and subsidiary of Pacific Life Re (PL Re), a global life and pensions reinsurance firm. We have a vision to help everyone purchase protection insurance by using data and disruptive technology to transform our partners and markets in order to make their underwriting processes as quick and efficient as possible. Our core products are: a best-in-market Underwriting Rules Engine which can be used to automate any structured data within the underwriting journey, and which is sold in the UK & Ireland, Asia-Pacific and North America the Protection Platform, an end-to-end quote and buy marketplace for Protection in the UK Working for UnderwriteMe Joining UnderwriteMe means being part of a technology company that is committed to bringing a fresh and dynamic approach to insurance. You'd be working with a team of highly technical experts made up of people with backgrounds in software, fintech, and insurance. Every person in our global team is valued for the unique qualities they bring to our business and we seek to build their expertise and support their individual ambitions at every step. Of course, we take our work seriously and we know our team can operate under great pressure. We work hard and thrive on achievement, but we also know how to have fun and relax too. We regularly host a range of team building days to strengthen our team's connection with each other and reflect on their successes. Providing employees with a healthy work-life balance is very important to our culture. We have a wide range of employee benefits and we host regular social activities and wellbeing initiatives. We are also committed to supporting our employee's involvement in their communities, by actively fundraising, hosting charity events . click apply for full job details
Mindgard is a London-based startup specializing in AI security. We've spun out from a leading UK university, and our mission is to secure the future of AI against cyber attacks targeting Deep Learning, GenAI, and LLMs. This is an unsolved challenge globally, and we are among the world's first to offer a solution to this rapidly growing problem. We've raised $4M from an excellent group of investors, released our first product offering: Mindgard AI Security Labs, and continue to build a team of engineers to join us on our journey. We're seeking a Research Scientist to join our R&D team, who is passionate about working on practical security problems within AI/ML. What You Will Be Doing Design, evaluate, and implement adversarial ML attacks and detection techniques. Work and collaborate with the R&D and engineering teams to push/translate adversarial ML techniques into production software for AI red teaming. Uncover ML security threats, analyze data and discover feature commonality. Engage in research collaboration, publications, and conference attendance. Keep the company updated on state-of-the-art research in adversarial ML. Who You Are PhD in Computer Science, with a specialization within AI/ML security and/or adversarial ML. An excellent track record of high-quality publications in top AI/ML or cyber security venues. We care about quality over quantity, and research that has industry application. Good programming skills in languages such as Python. Ability to supervise PhD students. We have a cohort of PhD students that you would have the opportunity to work and publish with. Optimism, kindness, and excellent communication skills. Ability to lead and contribute to research projects. Benefits Competitive salary 33 days vacation Flexible working options Learning & development budget Company equity Our Selection Process An initial call to help you get to know us better and to share more information about Mindgard and the role. A challenge related to the job. This will really help us understand your skillset and give you an idea of the type of things you will be working on at Mindgard. An opportunity to meet with a few members of the Mindgard team. An interview with our Co-founder. Offer Before you go, we want you to know! Studies have shown that some groups of people are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you don't meet all of the above criteria, but you think you'd be a great addition to Mindgard, we encourage you to apply as you might just be the candidate we hire. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone. Company: Mindgard Qualifications: Senior (5+ years of experience) Tagged as: Academia , NLP , United Kingdom
Feb 13, 2025
Full time
Mindgard is a London-based startup specializing in AI security. We've spun out from a leading UK university, and our mission is to secure the future of AI against cyber attacks targeting Deep Learning, GenAI, and LLMs. This is an unsolved challenge globally, and we are among the world's first to offer a solution to this rapidly growing problem. We've raised $4M from an excellent group of investors, released our first product offering: Mindgard AI Security Labs, and continue to build a team of engineers to join us on our journey. We're seeking a Research Scientist to join our R&D team, who is passionate about working on practical security problems within AI/ML. What You Will Be Doing Design, evaluate, and implement adversarial ML attacks and detection techniques. Work and collaborate with the R&D and engineering teams to push/translate adversarial ML techniques into production software for AI red teaming. Uncover ML security threats, analyze data and discover feature commonality. Engage in research collaboration, publications, and conference attendance. Keep the company updated on state-of-the-art research in adversarial ML. Who You Are PhD in Computer Science, with a specialization within AI/ML security and/or adversarial ML. An excellent track record of high-quality publications in top AI/ML or cyber security venues. We care about quality over quantity, and research that has industry application. Good programming skills in languages such as Python. Ability to supervise PhD students. We have a cohort of PhD students that you would have the opportunity to work and publish with. Optimism, kindness, and excellent communication skills. Ability to lead and contribute to research projects. Benefits Competitive salary 33 days vacation Flexible working options Learning & development budget Company equity Our Selection Process An initial call to help you get to know us better and to share more information about Mindgard and the role. A challenge related to the job. This will really help us understand your skillset and give you an idea of the type of things you will be working on at Mindgard. An opportunity to meet with a few members of the Mindgard team. An interview with our Co-founder. Offer Before you go, we want you to know! Studies have shown that some groups of people are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you don't meet all of the above criteria, but you think you'd be a great addition to Mindgard, we encourage you to apply as you might just be the candidate we hire. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone. Company: Mindgard Qualifications: Senior (5+ years of experience) Tagged as: Academia , NLP , United Kingdom
We are hiring for this role in London, Zurich, New York, Mountain View or San Francisco. Please clarify in the application questions which location(s) work best for you. At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. Snapshot Our team is responsible for enabling AI systems to reliably work as intended, including identifying potential risks from current and future AI systems, and conducting technical research to mitigate them. As a Research Scientist, you will design, implement, and empirically validate approaches to alignment and risk mitigation, and integrate successful approaches into our best AI systems. About Us Conducting research into any transformative technology comes with responsibility to build mechanisms for safe and reliable development and deployment at every step. Technical safety research at Google DeepMind investigates questions related to evaluations, reward learning, fairness, interpretability, robustness, and generalisation in machine learning systems. Proactive research in these areas is essential to the fulfilment of the long-term goal of Google DeepMind: to build safe and socially beneficial AI systems. Research Scientists work on the forefront of technical approaches to designing systems that reliably function as intended while discovering and mitigating risks, in close collaboration with other AI research groups within and outside of Google DeepMind. Our culture We're a dedicated scientific community, committed to 'solving intelligence' and ensuring our technology is used for widespread public benefit. We've built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don't set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals. We constantly iterate on our workplace experience with the goal of ensuring it encourages a balanced life. From excellent office facilities through to extensive manager support, we strive to support our people and their needs as effectively as possible. Roles We are seeking research scientists for our Gemini Safety and AGI Safety & Alignment (ASAT) teams. Gemini Safety Gemini Safety is seeking research scientists to contribute to the following areas: Pretraining In this role you will investigate new techniques to improve the safety behavior of Gemini via pretraining interventions. You will conduct empirical studies on model behavior, analyze model performance across different scales, experiment with synthetic datasets, data weighting, and related techniques. You should enjoy working with very large scale datasets and have an empirical mindset. Text output (core Gemini, reasoning models, Search AI mode, etc) This role is focused on post training safety. You will be part of a very fast paced, intense effort at the heart of Gemini to improve safety and helpfulness for the core model, and help adapt the model to specific use cases such as reasoning or search. Red teaming and adversarial resilience In this role, you will build and apply automated red teaming via our most capable models, find losses and vulnerabilities in our Gen AI products, including Gemini itself, reasoning models, image and video generation, and whatever else we are building. You may also work to improve resilience to jailbreaks and adversarial prompts across models and modalities, driving progress on a fundamentally unsolved problem with serious implications for future safety. Image and video generation This role is about safety for image and video generation, including Imagen, Veo, and Gemini. You will design evaluations for safety and fairness, improve the safety behavior of the relevant models working closely with the core modeling teams, and design mitigations outside the model (e.g. external classifiers). AGI Safety & Alignment (ASAT) Our AGI Safety & Alignment team is seeking research scientists to contribute to the following areas. Applied Interpretability The focus of this role is to put insights from model internals research into practice on both safety in Gemini post-training and dangerous capability evaluations in support of our Frontier Safety Framework . Key responsibilities: Rapid research ideation, iteration and production implementation of interpretability applications to address promising use cases. Adapting techniques emerging from collaboration with mechanistic interpretability researchers, as well as using other approaches such as probing and training data attribution. Inventing novel methods to address novel frontier AI advances. AGI Safety Research In this role you will advance AGI safety & alignment research within one of our priority areas. Candidates should have expertise in the area they apply to. We are also open to candidates who could lead a new research area with clear impact on AGI safety & alignment. Areas of interest include, but are not limited to: Dangerous Capability Evaluations: Designing evaluations for dangerous capabilities for use in the Frontier Safety Framework , particularly for automation of ML R&D Safety cases: Producing conceptual arguments backed by empirical evidence that a specific AI system is safe Alignable Systems Design: Prototyping AI systems that could plausibly support safety cases Externalized Reasoning: Understanding the strengths and limitations of monitoring the "out loud" chain of thought produced by modern LLMs Amplified Oversight: Supervising systems that may outperform humans Interpretability: Understanding the internal representations and algorithms in trained LLMs, and using this knowledge to improve safety Robustness: Expanding the distribution on which LLMs are trained to reduce out-of-distribution failures Monitoring: Detecting dangerous outputs and responding to them appropriately Control Evaluations: Designing and running red team evaluations that conservatively estimate risk from AI systems under the assumption that they are misaligned. Alignment Stress Testing: Identifying assumptions made by particular alignment plans, and red teaming them to see whether they hold About you You have extensive research experience with deep learning and/or foundation models (for example, a PhD in machine learning). You are adept at generating ideas and designing experiments, and implementing these in Python with real AI systems. You are keen to address risks from foundation models, and have thought about how to do so. You plan for your research to impact production systems on a timescale between "immediately" and "a few years". You are excited to work with strong contributors to make progress towards a shared ambitious goal. With strong, clear communication skills, you are confident engaging technical stakeholders to share research insights tailored to their background. In addition, any of the following would be an advantage: PhD in Computer Science or Machine Learning related field. A track record of publications at venues such as NeurIPS, ICLR, ICML, RL/DL, EMNLP, AAAI and UAI. Experience in areas such as Safety, Fairness and Alignment. Engineering experience with LLM training and inference. Experience with collaborating or leading an applied research project. What we offer At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc. We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility). The US base salary range for this full-time position is between $136,000 - $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Application deadline: 12pm PST Friday 28th February 2025
Feb 13, 2025
Full time
We are hiring for this role in London, Zurich, New York, Mountain View or San Francisco. Please clarify in the application questions which location(s) work best for you. At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. Snapshot Our team is responsible for enabling AI systems to reliably work as intended, including identifying potential risks from current and future AI systems, and conducting technical research to mitigate them. As a Research Scientist, you will design, implement, and empirically validate approaches to alignment and risk mitigation, and integrate successful approaches into our best AI systems. About Us Conducting research into any transformative technology comes with responsibility to build mechanisms for safe and reliable development and deployment at every step. Technical safety research at Google DeepMind investigates questions related to evaluations, reward learning, fairness, interpretability, robustness, and generalisation in machine learning systems. Proactive research in these areas is essential to the fulfilment of the long-term goal of Google DeepMind: to build safe and socially beneficial AI systems. Research Scientists work on the forefront of technical approaches to designing systems that reliably function as intended while discovering and mitigating risks, in close collaboration with other AI research groups within and outside of Google DeepMind. Our culture We're a dedicated scientific community, committed to 'solving intelligence' and ensuring our technology is used for widespread public benefit. We've built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don't set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals. We constantly iterate on our workplace experience with the goal of ensuring it encourages a balanced life. From excellent office facilities through to extensive manager support, we strive to support our people and their needs as effectively as possible. Roles We are seeking research scientists for our Gemini Safety and AGI Safety & Alignment (ASAT) teams. Gemini Safety Gemini Safety is seeking research scientists to contribute to the following areas: Pretraining In this role you will investigate new techniques to improve the safety behavior of Gemini via pretraining interventions. You will conduct empirical studies on model behavior, analyze model performance across different scales, experiment with synthetic datasets, data weighting, and related techniques. You should enjoy working with very large scale datasets and have an empirical mindset. Text output (core Gemini, reasoning models, Search AI mode, etc) This role is focused on post training safety. You will be part of a very fast paced, intense effort at the heart of Gemini to improve safety and helpfulness for the core model, and help adapt the model to specific use cases such as reasoning or search. Red teaming and adversarial resilience In this role, you will build and apply automated red teaming via our most capable models, find losses and vulnerabilities in our Gen AI products, including Gemini itself, reasoning models, image and video generation, and whatever else we are building. You may also work to improve resilience to jailbreaks and adversarial prompts across models and modalities, driving progress on a fundamentally unsolved problem with serious implications for future safety. Image and video generation This role is about safety for image and video generation, including Imagen, Veo, and Gemini. You will design evaluations for safety and fairness, improve the safety behavior of the relevant models working closely with the core modeling teams, and design mitigations outside the model (e.g. external classifiers). AGI Safety & Alignment (ASAT) Our AGI Safety & Alignment team is seeking research scientists to contribute to the following areas. Applied Interpretability The focus of this role is to put insights from model internals research into practice on both safety in Gemini post-training and dangerous capability evaluations in support of our Frontier Safety Framework . Key responsibilities: Rapid research ideation, iteration and production implementation of interpretability applications to address promising use cases. Adapting techniques emerging from collaboration with mechanistic interpretability researchers, as well as using other approaches such as probing and training data attribution. Inventing novel methods to address novel frontier AI advances. AGI Safety Research In this role you will advance AGI safety & alignment research within one of our priority areas. Candidates should have expertise in the area they apply to. We are also open to candidates who could lead a new research area with clear impact on AGI safety & alignment. Areas of interest include, but are not limited to: Dangerous Capability Evaluations: Designing evaluations for dangerous capabilities for use in the Frontier Safety Framework , particularly for automation of ML R&D Safety cases: Producing conceptual arguments backed by empirical evidence that a specific AI system is safe Alignable Systems Design: Prototyping AI systems that could plausibly support safety cases Externalized Reasoning: Understanding the strengths and limitations of monitoring the "out loud" chain of thought produced by modern LLMs Amplified Oversight: Supervising systems that may outperform humans Interpretability: Understanding the internal representations and algorithms in trained LLMs, and using this knowledge to improve safety Robustness: Expanding the distribution on which LLMs are trained to reduce out-of-distribution failures Monitoring: Detecting dangerous outputs and responding to them appropriately Control Evaluations: Designing and running red team evaluations that conservatively estimate risk from AI systems under the assumption that they are misaligned. Alignment Stress Testing: Identifying assumptions made by particular alignment plans, and red teaming them to see whether they hold About you You have extensive research experience with deep learning and/or foundation models (for example, a PhD in machine learning). You are adept at generating ideas and designing experiments, and implementing these in Python with real AI systems. You are keen to address risks from foundation models, and have thought about how to do so. You plan for your research to impact production systems on a timescale between "immediately" and "a few years". You are excited to work with strong contributors to make progress towards a shared ambitious goal. With strong, clear communication skills, you are confident engaging technical stakeholders to share research insights tailored to their background. In addition, any of the following would be an advantage: PhD in Computer Science or Machine Learning related field. A track record of publications at venues such as NeurIPS, ICLR, ICML, RL/DL, EMNLP, AAAI and UAI. Experience in areas such as Safety, Fairness and Alignment. Engineering experience with LLM training and inference. Experience with collaborating or leading an applied research project. What we offer At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc. We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility). The US base salary range for this full-time position is between $136,000 - $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Application deadline: 12pm PST Friday 28th February 2025
About Us At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We're here to change that. As former computer scientists, physicists, and quants, we've experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet-where the potential is clear, but the surrounding tools and processes are still catching up. That's why we started Encord. We are a talented and ambitious team of 60, working at the cutting edge of computer vision and deep learning. Backed by $30M in Series B funding from top investors like CRV and Y Combinator, we're one of the fastest-growing companies in our space. Our platform is consistently rated the best by our customers, and we have big plans ahead. We're looking for a Research Scientist to help our customers get the right data faster, easier, and cheaper. The Role As a Research Scientist focusing on multi-modal LLMs, you'll be allowing all the data, metadata, and embeddings that live in our system to be explored, used, and analyzed in ways no one thought possible. Although starting narrow with "smaller" multi-modal problems like, e.g., improving similarity searches via metadata, we have high ambitions for this role. You'll progressively work on harder problems that will improve user experience, surface the right (personalized) analytics to every customer, and put our users in the driver's seat of a data development platform that can do things much beyond today's standards. Tasks can be i) fine-tuning models to understand how our platform is used by customers, ii) employing LLM reasoning to assist customers in their data analysis tasks, and iii) Building tools for customers to interface naturally with our platform. All to put the power in the hands of anyone using Encord. You'll follow the latest research and accelerate state-of-the-art technologies to enrich customers' data journeys. This role offers a great growth opportunity, with the potential to lead a bigger team of scientists over time in our efforts to build the ultimate data development platform What you will be doing: Building, fine-tuning, and experimenting with multi-modal LLMs to surface potential actions and analytical conclusions in a data-driven manner. Developing scalable and novel ways to personalize LLMs based on information from our data development platform. Build sophisticated RAG systems on other types of data than the usual text documents. Follow the latest machine learning research to identify and apply new methods that improve our processes or the user experience. Ensure our customers have the world's most powerful AI-powered data development platform. Skills for the job: A PhD or similarly strong academic background in machine learning, with 2+ years of hands-on experience in with LLM fine-tuning, RAG systems, and prompt engineering. Proficiency with frameworks like PyTorch, Tensorflow, JAX, Pandas, and OpenCV. A solid understanding of transformer models and their common variants, loss functions, and pitfalls. A quick learner with a structured, organized approach to problem-solving. Excellent communication skills with an ability to uncover use cases and solve problems efficiently. Ambitious and self-motivated, with a proven track record of top performance in academic or professional settings. Bonus skills: Experience working with data in the order of millions. Familiarity with using (and adapting) models like LLaMa and LLaVa. Experience with image-to-text embedding models like CLIP and SigLIP. Familiarity with cloud-based model training and inference. What We Offer - Competitive salary, commission, and equity in a high-growth business. - A collaborative, in-person culture with most of the team working in the office 3+ days a week (engineers typically work on-site Wednesdays). - 25 days annual leave + public holidays. - An annual learning and development budget to help you grow your skills. - Company lunches twice a week and regular socials, including bi-annual off-sites. At Encord, you'll have the unique opportunity to be part of a fast-growing startup with a clear mission and vision. You'll work on real-world AI use cases across a variety of industry verticals and get hands-on experience with cutting-edge computer vision and deep learning technologies. This is a role where you'll grow quickly, take ownership of projects, and help shape the future of our company.
Feb 12, 2025
Full time
About Us At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We're here to change that. As former computer scientists, physicists, and quants, we've experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet-where the potential is clear, but the surrounding tools and processes are still catching up. That's why we started Encord. We are a talented and ambitious team of 60, working at the cutting edge of computer vision and deep learning. Backed by $30M in Series B funding from top investors like CRV and Y Combinator, we're one of the fastest-growing companies in our space. Our platform is consistently rated the best by our customers, and we have big plans ahead. We're looking for a Research Scientist to help our customers get the right data faster, easier, and cheaper. The Role As a Research Scientist focusing on multi-modal LLMs, you'll be allowing all the data, metadata, and embeddings that live in our system to be explored, used, and analyzed in ways no one thought possible. Although starting narrow with "smaller" multi-modal problems like, e.g., improving similarity searches via metadata, we have high ambitions for this role. You'll progressively work on harder problems that will improve user experience, surface the right (personalized) analytics to every customer, and put our users in the driver's seat of a data development platform that can do things much beyond today's standards. Tasks can be i) fine-tuning models to understand how our platform is used by customers, ii) employing LLM reasoning to assist customers in their data analysis tasks, and iii) Building tools for customers to interface naturally with our platform. All to put the power in the hands of anyone using Encord. You'll follow the latest research and accelerate state-of-the-art technologies to enrich customers' data journeys. This role offers a great growth opportunity, with the potential to lead a bigger team of scientists over time in our efforts to build the ultimate data development platform What you will be doing: Building, fine-tuning, and experimenting with multi-modal LLMs to surface potential actions and analytical conclusions in a data-driven manner. Developing scalable and novel ways to personalize LLMs based on information from our data development platform. Build sophisticated RAG systems on other types of data than the usual text documents. Follow the latest machine learning research to identify and apply new methods that improve our processes or the user experience. Ensure our customers have the world's most powerful AI-powered data development platform. Skills for the job: A PhD or similarly strong academic background in machine learning, with 2+ years of hands-on experience in with LLM fine-tuning, RAG systems, and prompt engineering. Proficiency with frameworks like PyTorch, Tensorflow, JAX, Pandas, and OpenCV. A solid understanding of transformer models and their common variants, loss functions, and pitfalls. A quick learner with a structured, organized approach to problem-solving. Excellent communication skills with an ability to uncover use cases and solve problems efficiently. Ambitious and self-motivated, with a proven track record of top performance in academic or professional settings. Bonus skills: Experience working with data in the order of millions. Familiarity with using (and adapting) models like LLaMa and LLaVa. Experience with image-to-text embedding models like CLIP and SigLIP. Familiarity with cloud-based model training and inference. What We Offer - Competitive salary, commission, and equity in a high-growth business. - A collaborative, in-person culture with most of the team working in the office 3+ days a week (engineers typically work on-site Wednesdays). - 25 days annual leave + public holidays. - An annual learning and development budget to help you grow your skills. - Company lunches twice a week and regular socials, including bi-annual off-sites. At Encord, you'll have the unique opportunity to be part of a fast-growing startup with a clear mission and vision. You'll work on real-world AI use cases across a variety of industry verticals and get hands-on experience with cutting-edge computer vision and deep learning technologies. This is a role where you'll grow quickly, take ownership of projects, and help shape the future of our company.
About Us At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We're here to change that. As former computer scientists, physicists, and quants, we've experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet-where the potential is clear, but the surrounding tools and processes are still catching up. That's why we started Encord. We are a talented and ambitious team of 60, working at the cutting edge of computer vision and deep learning. Backed by $30M in Series B funding from top investors like CRV and Y Combinator, we're one of the fastest-growing companies in our space. Our platform is consistently rated the best by our customers, and we have big plans ahead. We're looking for a Research Scientist to help our customers get the right data faster, easier, and cheaper. The Role As a Research Scientist focusing on multi-modal LLMs, you'll be allowing all the data, metadata, and embeddings that live in our system to be explored, used, and analyzed in ways no one thought possible. Although starting narrow with "smaller" multi-modal problems like, e.g., improving similarity searches via metadata, we have high ambitions for this role. You'll progressively work on harder problems that will improve user experience, surface the right (personalized) analytics to every customer, and put our users in the driver's seat of a data development platform that can do things much beyond today's standards. Tasks can be i) fine-tuning models to understand how our platform is used by customers, ii) employing LLM reasoning to assist customers in their data analysis tasks, and iii) building tools for customers to interface naturally with our platform. All to put the power in the hands of anyone using Encord. You'll follow the latest research and accelerate state-of-the-art technologies to enrich customers' data journeys. This role offers a great growth opportunity, with the potential to lead a bigger team of scientists over time in our efforts to build the ultimate data development platform. What you will be doing: Building, fine-tuning, and experimenting with multi-modal LLMs to surface potential actions and analytical conclusions in a data-driven manner. Developing scalable and novel ways to personalize LLMs based on information from our data development platform. Build sophisticated RAG systems on other types of data than the usual text documents. Follow the latest machine learning research to identify and apply new methods that improve our processes or the user experience. Ensure our customers have the world's most powerful AI-powered data development platform. Skills for the job: A PhD or similarly strong academic background in machine learning, with 2+ years of hands-on experience in LLM fine-tuning, RAG systems, and prompt engineering. Proficiency with frameworks like PyTorch, Tensorflow, JAX, Pandas, and OpenCV. A solid understanding of transformer models and their common variants, loss functions, and pitfalls. A quick learner with a structured, organized approach to problem-solving. Excellent communication skills with an ability to uncover use cases and solve problems efficiently. Ambitious and self-motivated, with a proven track record of top performance in academic or professional settings. Bonus skills: Experience working with data in the order of millions. Familiarity with using (and adapting) models like LLaMa and LLaVa. Experience with image-to-text embedding models like CLIP and SigLIP. Familiarity with cloud-based model training and inference. What We Offer - Competitive salary, commission, and equity in a high-growth business. - A collaborative, in-person culture with most of the team working in the office 3+ days a week (engineers typically work on-site Wednesdays). - 25 days annual leave + public holidays. - An annual learning and development budget to help you grow your skills. - Company lunches twice a week and regular socials, including bi-annual off-sites. At Encord, you'll have the unique opportunity to be part of a fast-growing startup with a clear mission and vision. You'll work on real-world AI use cases across a variety of industry verticals and get hands-on experience with cutting-edge computer vision and deep learning technologies. This is a role where you'll grow quickly, take ownership of projects, and help shape the future of our company.
Feb 12, 2025
Full time
About Us At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We're here to change that. As former computer scientists, physicists, and quants, we've experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet-where the potential is clear, but the surrounding tools and processes are still catching up. That's why we started Encord. We are a talented and ambitious team of 60, working at the cutting edge of computer vision and deep learning. Backed by $30M in Series B funding from top investors like CRV and Y Combinator, we're one of the fastest-growing companies in our space. Our platform is consistently rated the best by our customers, and we have big plans ahead. We're looking for a Research Scientist to help our customers get the right data faster, easier, and cheaper. The Role As a Research Scientist focusing on multi-modal LLMs, you'll be allowing all the data, metadata, and embeddings that live in our system to be explored, used, and analyzed in ways no one thought possible. Although starting narrow with "smaller" multi-modal problems like, e.g., improving similarity searches via metadata, we have high ambitions for this role. You'll progressively work on harder problems that will improve user experience, surface the right (personalized) analytics to every customer, and put our users in the driver's seat of a data development platform that can do things much beyond today's standards. Tasks can be i) fine-tuning models to understand how our platform is used by customers, ii) employing LLM reasoning to assist customers in their data analysis tasks, and iii) building tools for customers to interface naturally with our platform. All to put the power in the hands of anyone using Encord. You'll follow the latest research and accelerate state-of-the-art technologies to enrich customers' data journeys. This role offers a great growth opportunity, with the potential to lead a bigger team of scientists over time in our efforts to build the ultimate data development platform. What you will be doing: Building, fine-tuning, and experimenting with multi-modal LLMs to surface potential actions and analytical conclusions in a data-driven manner. Developing scalable and novel ways to personalize LLMs based on information from our data development platform. Build sophisticated RAG systems on other types of data than the usual text documents. Follow the latest machine learning research to identify and apply new methods that improve our processes or the user experience. Ensure our customers have the world's most powerful AI-powered data development platform. Skills for the job: A PhD or similarly strong academic background in machine learning, with 2+ years of hands-on experience in LLM fine-tuning, RAG systems, and prompt engineering. Proficiency with frameworks like PyTorch, Tensorflow, JAX, Pandas, and OpenCV. A solid understanding of transformer models and their common variants, loss functions, and pitfalls. A quick learner with a structured, organized approach to problem-solving. Excellent communication skills with an ability to uncover use cases and solve problems efficiently. Ambitious and self-motivated, with a proven track record of top performance in academic or professional settings. Bonus skills: Experience working with data in the order of millions. Familiarity with using (and adapting) models like LLaMa and LLaVa. Experience with image-to-text embedding models like CLIP and SigLIP. Familiarity with cloud-based model training and inference. What We Offer - Competitive salary, commission, and equity in a high-growth business. - A collaborative, in-person culture with most of the team working in the office 3+ days a week (engineers typically work on-site Wednesdays). - 25 days annual leave + public holidays. - An annual learning and development budget to help you grow your skills. - Company lunches twice a week and regular socials, including bi-annual off-sites. At Encord, you'll have the unique opportunity to be part of a fast-growing startup with a clear mission and vision. You'll work on real-world AI use cases across a variety of industry verticals and get hands-on experience with cutting-edge computer vision and deep learning technologies. This is a role where you'll grow quickly, take ownership of projects, and help shape the future of our company.
