1 to 25 of 1,488 Machine Learning Jobs in London

Learning Engineer to join a world-leading AI technology company developing cutting-edge software solutions. This is an ideal opportunity for an ML Engineer who has a strong academic background and experience working with LLM technologies. You will work alongside Software Engineers, Machine Learning specialists … Learning Engineer/Machine Learning Engineer/AI Engineer/Applied AI Engineer/Generative AI Engineer/LLM Engineer/ML Software Engineer/AI Software Engineer/Machine Learning Software Engineer/ML Infrastructure Engineer/Model Deployment Engineer/AI Integration Engineer ...

Description NLP/LLM Scientist – Applied AI ML Lead – Machine Learning Centre of Excellence The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, large language models … LLMs or recommendation systems Produce outputs that lead to high‐impact business applications, open‐source software, patents, and publications in top AI/ML conferences and journals. Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production Develop ...

Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs. The Machine Learning lead is expected to lead … ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise ...

across the organization. The position will be based out of our London or Manchester office. Specific Emerging Technology team objectives are: Gen AI/ML technology implementation with business and product owners Emerging Tech Governance function covering policies, guidelines and processes to govern AI/ML enabled components as well … vendor evaluations and tool assessments for relevant use cases. Where appropriate, onboard the right solutions into the platform. Effectively communicate advanced data science/ML concepts in simple language to the business stakeholders always focusing on its applicability to Fitch business Develop and deploy machine learning ...

build, and deploy machine learning and statistical models using Azure Machine Learning Studio (AML Studio) in production environments. Apply appropriate ML techniques to improve predictions such as longevity, default risk, and investment outcomes. Machine Learning Operations (MLOps in Azure) Manage the full ML life … cycle using Azure ML Studio, including deployment, monitoring, retraining pipelines, and version control. Implement robust MLOps practices such as model drift detection, data quality monitoring, and automated retraining workflows. Data Engineering and Preprocessing Develop and maintain scalable data pipelines using Python, SQL, and Azure Data Factory (ADF). Ensure data ...

Generative AI solutions that deliver real-world impact. Working alongside Data Scientists, Software Engineers and stakeholders, you'll help shape and deploy scalable ML solutions, taking projects from experimentation through to production while helping organisations unlock the value of AI responsibly and effectively. What We Can Offer … powered solutions Lead experimentation cycles, including hypothesis development, testing and evaluation Transition successful models from proof of concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible ...

intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As an Applied AI ML Director - NLP/LLM and Graphs within the Chief Data & Analytics Office, Machine Learning Centre of Excellence, you will have the opportunity … apply sophisticated machine learning methods to complex tasks including natural language processing, graph analytics, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly ...

Principal Research Scientist - Machine Learning London, United Kingdom IMC is one of the world’s leading trading firms, combining quantitative research, technology and trading expertise to solve complex problems at scale. As Machine Learning becomes increasingly important within our Systematic Equities business, we are investing … learning community. Responsibilities Shape the long‐term machine learning research agenda within Systematic Equities. Identify and translate advances from frontier ML research into practical opportunities. Conduct original research and develop proof‐of‐concept solutions where appropriate. Advise and mentor quantitative researchers on methodology, experimentation and research ...

intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As an Applied AI ML Director - NLP/LLM and Graphs within the Chief Data & Analytics Office, Machine Learning Centre of Excellence, you will have the opportunity … apply sophisticated machine learning methods to complex tasks including natural language processing, graph analytics, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly ...

Mode of Working: Hybrid Working Hours: 40 hours per week (Full-time) Are you looking to utilise your experience and expertise in AI, Machine Learning, and Advanced Analytics? We have an exciting opportunity for you - AI Engineer – Data & Reporting ! Careers at TCS: It Means More … APIs, SDKs, and microservices that integrate AI, RAG, and machine learning capabilities into enterprise applications. Own the end-to-end AI/ML lifecycle, including problem definition, data exploration, model development, validation, deployment, and monitoring. Develop forecasting models, segmentation strategies, optimisation algorithms, and early warning systems to support ...

MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software Engineers, Data Scientists, Product Managers and stakeholders across Trainline. Responsibilities Build and lead a new team of MLOps Engineers, creating an environment … product and data teams to bring strong engineering standards into machine learning delivery, while recognising the specific challenges of data, AI and ML systems. Support the productionisation of batch and online machine learning models, including recommendation systems, classification and regression models, large language models and agent ...

deliver for our clients. As a Customer AI Developer Specialist, you will: Play a key part in delivering impactful Machine Learning (ML) and Generative AI solutions across a variety of industries and use cases. From solving complex business problems to deploying scalable AI models, you'll operate … intersection of data science, technology, and business strategy. Key responsibilities: Machine Learning (ML) & AI Development · Solve business challenges using advanced ML techniques such as deep learning and quantitative analytics · Design and run experiments with generative AI models across text, images, audio, and video · Consult on and implement ...

manager is more interested in strong Machine Learning Engineers who understand production systems, infrastructure and engineering fundamentals. Candidates who have built traditional ML applications and have been actively developing their knowledge of LLMs will be strongly considered. They are looking for someone who can operate independently, take ownership … team days, with flexibility over the third day This would suit a Senior Machine Learning Engineer who wants genuine ownership of production ML, exposure to both established models and modern generative AI, and the opportunity to solve engineering problems at substantial real‐world scale. Please apply or message ...

Focus), you’ll act as the specialist technical authority within your discipline — helping shape the architecture, technical direction, and implementation strategy behind our ML‐driven products and platforms. You’ll work closely with Machine Learning Engineers, Tech Leads, Product teams, and other Team Architects to design intelligent … guide technical implementation across areas such as trajectory prediction, motion synthesis, real‐time data processing, 2D‐to‐3D geometry pipelines, and cloud‐hosted ML services. You’ll also ensure solutions are scalable, reusable, maintainable, and aligned with wider engineering standards across the business. What We Value You’ll fit right ...

seeking a Principal Research Scientist to help define and accelerate our long‐term machine learning research agenda. Prior finance experience is not required. The Role This role is designed for an established academic researcher or research scientist who wants to remain connected to the frontier of machine … learning community. Responsibilities Shape the long‐term machine learning research agenda within Systematic Equities. Identify and translate advances from frontier ML research into practical opportunities. Conduct original research and develop proof‐of‐concept solutions where appropriate. Advise and mentor quantitative researchers on methodology, experimentation and research ...

STEM discipline such as Computer Science, Mathematics, Physics, Engineering, or related fields Commercial experience developing machine learning solutions using Python and modern ML frameworks Strong understanding of applied machine learning techniques, particularly around modelling complex systems and large-scale datasets Experience working with time-series, forecasting … work autonomously within a fast-moving environment Interest in applying machine learning to operational, industrial, or physical systems Desirable Experience Experience deploying ML systems into production environments Exposure to scientific machine learning, simulation, or reinforcement learning Familiarity with cloud infrastructure and scalable ML pipelines ...

This is a role for someone who wants to build category-defining technology rather than incremental improvements. Why This Role Stands Out Most senior ML opportunities offer scale. Few offer ownership. Here, you'll have the opportunity to: Define the machine learning architecture that powers the entire product. … visible impact, opportunities like this are rare. What You'll Own You will lead the design, development, and operation of the company's core ML systems, including: Machine Learning Infrastructure End-to-end training pipelines Evaluation and benchmarking frameworks Production inference architecture Monitoring, observability, and performance systems Deployment ...

This is a role for someone who wants to build category-defining technology rather than incremental improvements. Why This Role Stands Out Most senior ML opportunities offer scale. Few offer ownership. Here, you'll have the opportunity to: Define the machine learning architecture that powers the entire product. … visible impact, opportunities like this are rare. What You'll Own You will lead the design, development, and operation of the company's core ML systems, including: Machine Learning Infrastructure End-to-end training pipelines Evaluation and benchmarking frameworks Production inference architecture Monitoring, observability, and performance systems Deployment ...

Machine Learning Research Engineer - Deep Learning Location: Farringdon, London (Typically 2 days per week in the office) Salary: Up to £110,000 + 10% Bonus The Opportunity We're working with a growing technology business that's using advanced AI to solve complex real-world engineering problems. … They're looking for an Applied Scientist to join their R&D function, where the focus is on researching and developing novel deep learning approaches to tackle problems that don't have an obvious solution. This is a role for someone who enjoys understanding complex systems, experimenting with ...

Months long The Company They are a data-driven consulting and analytics organisation that helps clients make smarter decisions through advanced measurement, machine learning, and AI solutions. Their teams work across data, analytics, engineering, and consulting disciplines to solve complex business challenges. They foster a collaborative environment where … advanced machine learning and AI solutions that drive measurable business outcomes. Develop, optimise, and deploy machine learning models and scalable ML pipelines. Build and maintain machine learning infrastructure, ensuring strong governance, version control, and model lifecycle management. Apply advanced statistical modelling and experimentation techniques ...

company that's scaling its machine learning platform and is looking for a Machine Learning Systems Engineer to help take ML models from research into reliable, production-ready systems. This is a hands-on engineering role focused on building the infrastructure, tooling and automation that enables … deployed, monitored and continuously improved across production environments. You'll work closely with Applied Scientists and Software Engineers to deliver scalable, resilient ML systems. The Role You'll play a key role in designing and operating the systems that underpin the ML lifecycle, including model training, deployment, serving and monitoring. ...

products. As part of the wider PDT leadership team, you’ll influence roadmap decisions, shape investment priorities, and act as the senior voice for ML and AI across the Cards business. Key Responsibilities Define the vision and direction for machine learning and AI across the Cards business, identifying … opportunities to improve customer experience and commercial performance Lead the performance and evolution of core ML systems including recommendations, ranking, search and personalisation Own model quality and lifecycle management, including evaluation, monitoring, retraining and long-term maintainability Drive the development of AI-powered product features, including LLM-based and generative ...

want practical exposure to AI-driven business solutions. This expert-led programme will help you understand how organisations evaluate, test, and improve AI/ML systems through AI assurance, data quality analysis, model risk evaluation, and real-world case studies. What You'll Learn ✔ AI & Machine Learning Fundamentals … reliability perspective ✅ Design AI testing and assurance strategies ✅ Identify situations where AI recommendations can or cannot be trusted ✅ Complete a real-world AI/ML case study and create an interview-ready portfolio project Who Should Apply? Recent graduates in Computer Science, Data Science, AI, Machine Learning ...

want practical exposure to AI-driven business solutions. This expert-led programme will help you understand how organisations evaluate, test, and improve AI/ML systems through AI assurance, data quality analysis, model risk evaluation, and real-world case studies. What You'll Learn ✔ AI & Machine Learning Fundamentals … reliability perspective ✅ Design AI testing and assurance strategies ✅ Identify situations where AI recommendations can or cannot be trusted ✅ Complete a real-world AI/ML case study and create an interview-ready portfolio project Who Should Apply? Recent graduates in Computer Science, Data Science, AI, Machine Learning ...

projects over the full lifecycle, from conception to data preparation, model engineering, evaluation and deployment and finally model monitoring and maintenance Establishing and developing ML Ops frameworks and standards for clients and embedding within their infrastructure Working with clients to take them on the journey, upskilling along … loop and can take ownership after you roll off the project Performing maturity assessments across clients’ Cloud/AI environments and recommending improvements Building ML strategy blueprints and advising clients on the different technology options Translating business requirements (both functional and non-functional) into solutions, ensuring compliance with the organisations ...