101 to 125 of 1,144 Machine Learning Jobs in London

Overview The Applied Innovation (of AI) Engineering team is an elite machine learning group strategically located within the Chief Data Analytics Office (CDAO) Technology group of JPMorgan Chase. AI Engineering tackles business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMorgan Chase businesses as they grow. Responsibilities Collaborates ...

quality measurement Embeddings, reranking, and retrieval orchestration Evaluation datasets, benchmarking, and annotation workflows Advanced programming skills in Python. Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack). Experience working with large-scale datasets, distributed data/ML platforms, and production AI systems. … assistants. Familiarity with scientific, biomedical, or scholarly datasets and workflows. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Exposure to production ML systems, MLOps, and AI governance practices. Publications or applied research contributions in NLP, IR, search, recommendation systems, or generative AI. Experience building AI systems in high-trust ...

impact. You will also collaborate across teams to turn complex challenges into practical, production-ready solutions. Responsibilities Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question … experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field. Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems in applied or product-focused environments. Expertise working with LLMs, including fine-tuning, prompt engineering, grounding strategies ...

Machine Learning Engineer, NLP | InsurTech, AI, Scale-up | London 5 Days in Office, Up to £165,000 Stocks & Benefits. Owen Thomas is partnering with a high‐growth, venture‐backed InsurTech scale‐up that is disrupting a massive $200 B global market. Using AI they deliver automation that … founding team, learning exactly how to scale a business from 0 to 1. Requirements 2+ years of commercial experience in AI/ML engineering or applied research. Strong experience working on NLP projects. A proven track record of shipping AI/ML projects from initial concept to live production ...

Senior Data Scientist LOCATION- London (Hybrid) TERM- Permanent SALARY- £85,000 to £95,000 per annum BENEFITS Pension, Hybrid Working, Learning & Development Budget, Private Healthcare, Bonus, Career Progression Opportunities etc. We are partnering with a highly regarded, technology-driven organisation that is investing heavily in data, machine learning … Scientist MUST have: Several years of hands-on Data Science experience within a commercial environment Strong Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience ...

insurance. Excited to make an impact? Here are the details What you will do Define model development methodologies and best practices across the entire ML lifecycle Play a central role in selecting and evolving the technological stack Support the productionalization and evolution of the Oracles — entities that leverage machine … with emerging technologies What we’re looking for Core Skills & Experience Strong programming background with deep expertise in Python Experience across the lifecycle of ML model development, including production deployment Proficiency in software development practices such as: TDD BDD Commitment to code quality, readability, and maintainability Extensive experience in software ...

with cross-functional teams to design, develop and deploy advanced AI models, with a particular focus on Large Language Models (LLMs), AI agents and machine learning technologies. The Role As Principal AI Scientist, you will be the technical authority for AI research and innovation. You'll define … technical research initiatives and defining AI strategy. Experience taking AI solutions from research through to production. Excellent Python programming skills. Strong understanding of modern ML frameworks such as PyTorch or TensorFlow. Experience evaluating AI model performance and designing robust experimentation methodologies. Psychometric Experience You'll either have direct experience ...

London, with hybrid working available. This organisation has established itself as a leader within the consumer finance and technology sector, combining advanced analytics, machine learning and cutting-edge technology to drive intelligent decision-making and responsible lending. Operating within a collaborative, high-growth environment, they are committed … will not be limited to : Developing and maintaining robust data solutions to support predictive modelling and advanced analytical projects Designing, building and deploying machine learning models to support credit risk management and wider business optimisation initiatives Deploying predictive models into production environments, collaborating closely with software engineering teams ...

Loyalty.This is an opportunity to lead a talented team whilst remaining hands-on, solving some of our biggest customer, marketing and commercial challenges using Machine Learning and advanced analytics.Working across multiple product value streams, you'll partner with Product Owners, Engineers, Analysts and business leaders to identify where … combine technical leadership with commercial thinking, leading a team of Data Scientists whilst remaining hands-on in the design and delivery of production-ready Machine Learning solutions. Spending around half of your time on technical delivery, you'll coach your team, set technical standards and ensure Data Science ...

provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … strategic direction of our ML platform—spanning data pipelines, model development, deployment automation, inference runtime design, telemetry, drift detection, and cross‐account productionisation. You will mentor engineers, influence product and architectural decisions, and ensure that our ML systems operate reliably at scale, underpinned by a robust governance and compliance framework. ...

Data Science Manager | Logistics, Autopanner | Hybrid Working | London & Hatfield Introduction Ocado Technology is changing the way the world shops using advanced Artificial Intelligence, Machine Learning, Robotics, Big Data, Cloud and IoT. We develop the innovative software and hardware systems that power Ocado.com, as well as the unique ‘Ocado … Responsibilities Lead a multidisciplinary team of data scientists and software engineers to research, develop, and deploy sophisticated planning systems. Drive the development of machine learning solutions focused on predicting and optimising route requirements, staffing needs, and sales estimations. Identify new opportunities to add business value through machine ...

apply, and the type of support you need to complete the application to adjustments@depop.com. Role Depop is looking for a talented Staff ML Scientist to join our Ranking ML team in the UK. You will work alongside a cross-functional team of Product Managers, ML Engineers, and fellow ML … partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes. Lead the end-to-end lifecycle of ML projects: from ideation, data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration. Drive innovation in ranking by researching and integrating emerging ML ...

into a proper management role over time. This is not a pure manager role from day one. You’ll be building, shipping, and improving ML systems while gradually taking on more team leadership responsibilities. Key Responsibilities What you’ll do: Build and maintain production‐grade ML systems and pipelines Stay … hands‐on (coding, reviews, debugging, deployments) Mentor a small team of ML engineers (2–3 people initially) Establish ML engineering & MLOps best practices Improve deployment, monitoring, and model lifecycle management Collaborate with DS, Risk, Product, and Engineering Help shape roadmap and hiring Skills, Knowledge & Expertise Strong background as an ML ...

Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Manager in SAIL, you will own and lead consultancy engagements … winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients. Although we do not expect ...

Senior AI/ML Computational Scientist YOU ARE If you're a senior AI/ML Computational Scientist, you will design, build, and operationalize AI and ML solutions for enterprise clients, combining custom models with cloud and third‐party AI services to deliver production-ready outcomes. Your role spans … include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks. Established experience in building and deploying AI/ML based software to a cloud environment. PREFERRED QUALIFICATION Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks ...

advanced algorithms and training techniques for Large Language Models (LLMs). LLM Training (Continued pretraining, instruction tuning, reinforcement learning, distributed training, efficient ML techniques) Post-training techniques for planning, reasoning & complex workflows (e.g., reasoning models, LLMs + knowledge graphs, test time compute, CoT pipelines, tool use & API calling, etc. … demonstrated experience successfully managing software development teams in an agile environment. Experience spearheading technical development in a cross-functional setting, with responsibility for ML applications; close partnership with Applied Scientists, R&D groups, or similar. A portfolio showcasing significant contributions to technology innovation Excellent project management, organization and communication skills ...

Applied AI/ML Lead - Vice President - Machine Learning Engineer at JPMorgan Infrastructure Platform, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance … role is initially that of an individual contributor. Job Responsibilities Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions. Design and execute enterprise-wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development. Design and develop multi-agent systems ...

Applied AI/ML Lead – Vice President - Machine Learning Engineer at JPMorgan Infrastructure Platform, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance … role is initially that of an individual contributor. Job responsibilities: Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions. Design and execute enterprise-wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development. Design and develop multi-agent systems ...

agent ecosystems encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You will be accountable for ensuring the complete architecture meets the most rigorous non-functional requirements across security … strategy—adaptation, fine‐tuning, and dynamic cost/quality/latency‐aware routing Set the standards for high‐throughput, low‐latency inferencing and classical ML deployment within unified, production‐ready platforms Own the architecture of the enterprise context layer—knowledge graphs, ontologies, vector search, and semantic retrieval—grounding the solution ...

About the Role Level: 4 Department: COO Location: Southampton or London Contract type: Permanent Key Accountabilities AI/ML Solution Delivery: Hands on end-to-end development and deployment of both traditional and GenAI-based machine learning models, including discovery analytics, experimental design, model development, benchmarking, enhancement … production-ready AI systems. Domain expertise in financial services or other regulated industries is highly desirable. Experience: Strong experience in AI/ML research and development, specializing in deep learning-based NLP, Information Retrieval, and Generative AI. Proven expertise in RAG/GraphRAG pipeline development and evaluation, including advanced ...

Group Functions, Retail and Investment Banking. On behalf of this organisation, AMS are looking for a Business/Data Analyst with strong experience in machine learning system implementation, for a 6 month contract (with potential for extension) based in the London office (hybrid model, 2 days a week … Business/Data Analyst will support the implementation of our client's transaction monitoring system from a legacy rules-based environment to a Machine Learning-driven AML platform. This role sits within the Product team and will play a key role in defining requirements, supporting model development ...

this key role,you’lllead the engineering of AI and machine learning(ML)capabilities for the Economic Crime Hub, translating decision strategies into scalable, production-grade solutions We’lllook to you to own the end-to-end lifecycle of AI andMLmodels, from development and deployment through to monitoring … andMLsolutionsoperatereliablyandsafelywithin governed,compliant environments, while meeting business, risk, and regulatory requirements Whatyou'lldo AsaAI Engineering Lead,you'lllead the design, build, and deployment of ML models and AI systems into production environments.You'lltranslate decision strategies and analytical requirements into production-grade solutions, designing reusable pipelines and frameworks that support efficient ...

About our team We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering—from predictive models to enterprise GenAI apps to automation that … machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations. In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation ...

expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial … that identify, categorize, and assess sustainability risks Own cross-team projects end-to-end, from research and experimentation through production deployment Research and train ML models that help investors assess and manage sustainability risks Design and build real-time NLP pipelines using large language models Develop evaluation frameworks and annotation ...

applications to build features that businesses rely on in real time. Your Impact Advanced Modeling: Design, train, and implement advanced Machine Learning (ML) and Deep Learning (DL) models to solve complex business planning and forecasting problems. Predictive & Timeseries Forecasting: Develop robust, scalable time-series models to enhance … professional experience in Artificial Intelligence, Machine Learning, or a highly quantitative field. Strong predictive modeling foundation with deep expertise in traditional ML algorithms and time-series forecasting. Hands-on GenAI experience: Practical experience with LLM APIs, prompt engineering, and fine-tuning open-source models. Production-grade Python: High ...