Top Machine Learning Jobs in London

Design and scale advanced analytics, statistical, machine learning, and AI solutions for Life Sciences customers across Europe. Integrate Veeva Data Cloud with healthcare datasets, build HCP precision-engagement models, translate technical insights into business value, collaborate with cross-functional teams, and document methodologies, architectures, and validation processes.

Leads research into foundation models and generative AI for medical imaging and radiology. Responsibilities include defining research roadmaps, designing novel multimodal architectures, building experimental systems, benchmarking clinical and technical tasks, collaborating on deployable solutions, publishing research, mentoring researchers, and engaging academic partners.

Own the strategy, roadmap, metrics, and adoption of JetBrains Context, a managed retrieval layer for AI coding agents. Partner with engineering, ML, platform, IDE, marketing, sales, and customer success teams to improve indexing, retrieval quality, integrations, reliability, cost, and latency. Define product direction, evaluate competitors, establish quality metrics, communicate with customers and developer communities, and drive enterprise adoption.

Develop and maintain production data science models for attribution, marketing mix modelling, incrementality testing, and brand impact measurement. Lead projects end to end, select modelling approaches, debug unfamiliar codebases, apply AI tooling, collaborate with QA, communicate technical findings to clients, and mentor junior colleagues. The role requires strong Python, SQL, machine learning, production engineering, stakeholder communication, and independent ownership.

Drive enterprise sales growth for Thomson Reuters legal and compliance software products. Develop account strategies, acquire and expand customers, manage strategic relationships, conduct consultative solution selling, lead complex presentations, and close high-value deals. Partner with specialists, marketing, customer success, professional services, and alliances teams to support renewals, onboarding, retention, upselling, and cross-selling. Manage sales pipelines and quotas using Salesforce while maintaining forecast accuracy and customer satisfaction.

Own the strategy and execution of AI-powered AML and compliance products, including screening, transaction monitoring, risk scoring, automation, and agentic workflows. Translate regulatory and commercial requirements into technical specifications, APIs, schemas, webhooks, and logic. Lead features from discovery through deployment and billing, improve detection accuracy and reduce false positives, create monetizable modules, and serve as the technical expert for clients and partners.

Leads WPP Media’s Paid Search function across strategic client portfolios in the UK. Responsibilities include managing senior teams, setting channel strategy and delivery standards, driving client growth and commercial performance, integrating Paid Search with SEO, content, analytics, commerce and AI search, championing automation and innovation, ensuring governance and quality, supporting new business, and representing the agency through thought leadership and industry engagement.

Drive enterprise sales growth for Thomson Reuters Tax and Trade products through new customer acquisition, upselling, cross-selling, and strategic account planning. Manage complex sales cycles, build executive customer relationships, lead tailored presentations, and meet revenue quotas. Collaborate with solution consultants, specialists, marketing, professional services, partnerships, and customer success teams while using Salesforce workflows and sales analytics to manage pipeline, forecast accurately, and close high-value opportunities.

Define, architect, and lead delivery of machine learning and AI solutions. Support exploratory data analysis, proofs of concept, and the end-to-end data science lifecycle. Translate business problems into analytical and modeling solutions, communicate findings to technical and non-technical stakeholders, and provide specialist model delivery support. Design, develop, test, implement, and monitor models while tracking advances in data science and advising leadership on competitive capabilities.

Provide scientific leadership for evaluating foundation models and applying machine learning to genomics, drug development, and translational research. Partner with research, product, and business development teams to create customer-focused workflows, mentor junior colleagues, translate complex science for varied stakeholders, and guide rapid prototype-to-insight experimentation.

Develop and support secure, scalable software for AI/ML data platforms. Responsibilities include Python architecture and development, cloud-native and containerized application delivery, code review, testing, troubleshooting, operational stability, and automation of recurring remediation. The role also promotes validated AI-assisted engineering practices and collaborates with product managers and data strategy teams. Preferred experience includes graph databases such as AWS Neptune and generative AI engineering pipelines.

Develops governed business intelligence solutions, including dashboards, semantic models, reports, and data visualizations, to support executive decision-making. Partners with product owners, engineers, architects, and business stakeholders to translate needs into analytical experiences. Mines data for trends, applies statistical analysis, supports AI-enabled analytics, and maintains consistent metric definitions. The role also emphasizes governance, risk management, controls, stakeholder communication, and user-friendly data products.

Own the roadmap and strategy for AI- and data-powered advertising products spanning ad targeting, creative optimization, and measurement. Lead development and data science teams, translate strategy into prioritized backlogs, define user stories, and guide products from concept through deployment. Use SQL with Snowflake or BigQuery for hands-on analysis, validate product hypotheses, prototype ideas, and collaborate with technical and commercial stakeholders to deliver measurable advertiser value.

Lead and grow a team of seven ML and data engineers delivering production machine learning, AI, recommendation, search, commerce, and agentic systems. Own hiring, performance, delivery, technical direction, architecture, MLOps, evaluation, monitoring, responsible AI, and stakeholder communication. Guide reliable data pipelines, model deployment, experimentation, LLM evaluation, and production agent systems using tools such as LangGraph and Amazon Bedrock.

The Marketplace Account Executive identifies and qualifies strategic prospects, engages stakeholders, communicates Pattern’s ecommerce value proposition, and drives complex B2B deals through the full sales cycle. Responsibilities include prospect research, relationship building, account planning, messaging, negotiation, meeting generation, and collaboration with enterprise account managers, marketing, and alliances teams. The role requires disciplined pipeline management, self-directed urgency, and comfort navigating long, multi-stakeholder sales cycles.

Analyze daily trading P&L, positions, risk reports, limits, and market risks for gas and other commodity desks. Support product approvals, risk committees, audits, trading procedure compliance, and Endur system changes. Enhance reporting and automate risk processes using Excel, VBA, SQL, Python, machine learning, and artificial intelligence while communicating findings to senior management and stakeholders.

Leads complex end-to-end Workday Financial Management implementations across UKI. Owns finance workstreams, facilitates requirements and solution design workshops, configures Workday Financials, leads testing and go-live activities, advises finance executives, supports sales and pre-sales efforts, mentors consultants, and applies AI-enabled approaches to improve financial processes.

Lead product vision, strategy, roadmap, discovery, prioritization, and success metrics for an enterprise AI governance and assurance platform. Align Product, Engineering, Sales, Pre-Sales, Field Deployment, leadership, and customers around outcomes. Build scalable product processes and capabilities, mentor the product team, and translate complex AI governance, regulatory, risk, compliance, and enterprise needs into focused product priorities.

Build and deploy production machine learning models, scalable ML infrastructure, real-time training and inference pipelines, multimodal AI systems, and model APIs. Optimize model performance for cost, speed, and accuracy while applying MLOps practices. Collaborate with data science teams to productionize research models and independently architect highly available ML systems for a global media and entertainment platform.

Lead high-impact AI product initiatives from discovery through launch, adoption, and iteration. Shape multi-quarter strategy and roadmaps, engage enterprise customers, define requirements with engineering and design, and align cross-functional stakeholders. Own success metrics, navigate technical tradeoffs involving LLMs, agents, data, and platform architecture, and mentor product managers. The role requires strategic judgment, technical credibility, customer empathy, and strong execution across ambiguous, multi-team problem spaces.

Lead Spotify’s Search Personalization strategy across ranking, relevance, retrieval, AI-native search, quality, and trust. Own the multi-cycle roadmap, guide AI-powered features such as semantic search and LLM reranking, establish search quality frameworks, and balance relevance, latency, cost, and freshness. Lead two search squads, influence architecture decisions, align stakeholders and executives, and mentor junior product managers across Spotify’s search platform.

Industrial placement roles in biostatistics, clinical programming, and quantitative sciences innovation. Responsibilities include clinical trial design, statistical analysis, dataset and reporting development, quality control, machine learning, prediction modeling, and cross-functional collaboration supporting drug and vaccine development. Placements involve R, SAS, Python, GitHub, statistical methods, regulatory standards, and agile project delivery.

Leads Ipsen’s statistical innovation strategy across R&D, including innovative trial design, simulation, advanced modeling, predictive analytics, digital twins, virtual controls, and data mining. Manages a specialist quantitative team, establishes methodological standards, supports regulatory and portfolio decisions, and partners with biostatistics, clinical development, data science, and other cross-functional groups. Develops talent, oversees reproducible and submission-ready methods, and builds external scientific networks.

Develop and deploy learning-based locomotion and whole-body control policies for humanoid robots. Build motion primitives, simulation and training pipelines, and sim-to-real transfer methods using reinforcement learning, imitation learning, and generative models. Integrate and optimize learned policies for real-time robotic control, then evaluate and debug them on physical robots in collaboration with robotics, controls, simulation, and machine learning teams.

Build and own full-stack internal tooling and creator-facing workflows for AI-powered games. Translate the needs of designers, artists, writers, engineers, and external partners into intuitive, scalable applications and narrative systems. Collaborate across disciplines, iterate based on developer feedback, and write performant, maintainable production code with significant end-to-end ownership.