Top Machine Learning Jobs in London

Develop and maintain Elasticsearch’s Inference API and plugin framework, integrating internal and external AI providers. Responsibilities include API and protocol design, streaming, asynchronous execution, rate limiting, configuration, billing integration, error handling, open-source contribution reviews, incident response, and comprehensive unit, REST, and rolling-upgrade testing. The role requires advanced Java expertise, concurrency and parallelism knowledge, API design skills, cross-functional collaboration, and autonomous work in a distributed team.

Own Quince’s international forecasting and replenishment architecture, combining classical forecasting, machine learning, and AI agents. Build prototypes and analytical tools in Python, SQL, and Streamlit; partner with data and engineering teams to productionize successful solutions. Improve forecast accuracy, reduce stockouts, automate planning workflows, support new-market launches, and translate between planners, engineers, and leadership. Establish trusted human-machine decision processes and continuously improve planning systems across international markets.

Lead the architecture and production delivery of large-scale machine learning systems for personalized recommendations, search relevance, outfit discovery, and AI Stylist experiences. Set technical direction across ML platforms, ranking, retrieval, deep learning, generative AI, and MLOps. Partner with scientists, engineers, product managers, and senior stakeholders; drive scalable, reliable systems; mentor senior engineers; and establish engineering standards across teams.

Build infrastructure and pipelines for machine learning models deployed across unmanned vehicle fleets. Responsibilities include dataset curation, secure operational data collection, annotation, synthetic data generation, training, evaluation, inference optimization, and edge deployment. The role requires Python, MLOps, backend development, large-dataset handling, and the ability to work across the full ML systems stack.

Build and operate production machine learning systems for global document classification and extraction. Design training, evaluation, labeling, and deployment pipelines; optimize GPU inference for real-time performance; and integrate VLM/LLM and traditional ML capabilities into identity verification products. Lead technical designs, improve scalability and reliability, guide releases, review code, mentor engineers, and coordinate cross-functional solutions.

Own the analytical layer for autonomous-driving model evaluation and release decisions. Analyze simulation and on-road experiment data, improve performance metrics and scoring methods, identify measurement gaps, apply statistical rigor, and translate investigations into actionable recommendations. Partner with Data Science, Validation, Product, engineering, and OEM teams to strengthen evaluation coverage, ground truth, quality investigations, and weekly model-release feedback loops.

Manage regional field marketing across Middle Eastern markets from the UK. Plan and execute sponsorships, conferences, executive events, roundtables, customer experiences, account-based marketing activations, and country launches. Responsibilities include venue sourcing, vendor management, logistics, branding, invitations, attendee management, on-site delivery, post-event follow-up, and collaboration with Sales, Growth, and country leadership to support strategic accounts and pipeline growth.

Leads complex Defence and national security programmes spanning AI strategy, R&D, digital product development, and deployment. Oversees portfolios, develops growth proposals, mentors teams, manages senior military and civilian relationships, and advises clients on AI implementation and operational outcomes. Requires substantial Defence experience, transformation programme leadership, digital product delivery, commercial consulting expertise, and UK Security Clearance eligibility. The role involves working onsite with UK customers two to four days weekly and travelling throughout the UK when required.

Leads Tide’s global KYX engineering organization across onboarding, continuous due diligence, identity, risk scoring, data science, and ML. Owns engineering strategy, organization design, model lifecycle, regulated AI deployment, and measurable improvements in conversion, due diligence quality, automation, and servicing costs. Partners with operations, policy, risk, compliance, product, and IAM teams across multiple markets while building globally reusable platforms with market-specific logic isolated.

Leads end-to-end development and production deployment of machine learning, generative AI, and agentic solutions for payments and banking. Responsibilities include problem framing, experimentation, evaluation, MLOps, LLMOps, governance, monitoring, scalable cloud architecture, security, and systems integration. The role establishes reusable AI capabilities, partners with cross-functional stakeholders, mentors technical teams, and communicates model outcomes and operational tradeoffs to technical and non-technical audiences.

Build, maintain, and monitor live trading infrastructure; develop research platforms and analytics tools; and collaborate with quantitative researchers to productionize trading strategies. The role involves greenfield development, system enhancement, refactoring, and exposure to trading and research platforms. Candidates should have strong software engineering, numerical reasoning, and problem-solving skills, with proficiency in a modern programming language and interest in quantitative research, machine learning, cloud platforms, and emerging development technologies.

Leads the strategic direction of independent medical education and scientific content solutions. Provides clinical oversight, develops evidence-based content strategies and therapeutic plans, ensures medical accuracy and defensibility, and partners with editorial, product, project, commercial, and scientific stakeholders. The role monitors clinical evidence and regulatory developments, advises on complex content decisions, engages key opinion leaders and customers, and translates complex medical and scientific information into accessible educational products.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Supports BIM and advanced Revit workflows across architectural projects, including project setup, model coordination, audits, clash detection, CDE governance, documentation, and digital handover. Develops and implements AI-assisted, automated, and data-driven workflows connected to BIM, IFC, and interoperability processes. Provides Revit troubleshooting, training, standards development, and knowledge sharing while contributing to the practice’s digital technology strategy.

Lead the development and execution of the company’s long-term technology strategy and roadmap. Assess emerging technologies, especially AI and machine learning, and translate insights into investment recommendations and business cases. Advise executives, prepare board materials, support technology planning and supplier negotiations, and collaborate across business functions. The role also contributes to transformation programs, mergers and acquisitions, technology due diligence, and integration planning while influencing stakeholders without direct management authority.

Build, maintain, monitor, and improve technical pricing models for insurance portfolios using statistical and machine-learning techniques. Produce standardized data models, reporting, and pricing insights; compare predicted and actual performance; recommend model updates; and influence underwriting decisions and profitable growth. The role requires stakeholder management, collaboration on data and pricing technologies, accountability for model performance, and coaching junior analysts.

Lead programme-level project management for an osteoporosis discovery programme, coordinating interdisciplinary internal teams and CROs, translating scientific goals into integrated plans, managing budgets, risks, governance, and resource allocation, and communicating status to leaders and partners to drive timely milestone-based progression through discovery stages.

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.