Top Machine Learning Jobs in London

The Staff Data Scientist will provide technical leadership in Claims, developing ML and AI systems for risk decisioning and fraud detection, collaborating with cross-functional teams to scale decisioning and enhance claims automation.

Lead technical strategy for claims fraud data science, designing and shipping production ML and Generative AI/LLM systems. Drive system-level improvements for model integration, monitoring, feedback loops and QA. Influence cross-functional product and engineering decisions to scale AI-driven claims automation and improve measurement of performance and uncertainty.

Lead trust and safety for an AI mental-health product by developing policies, investigating risks and user reports, building response processes, and translating findings into product improvements. Collaborate with clinical, legal, research, engineering, and machine-learning teams. Communicate safety principles and evaluations internally and externally, establish benchmarks, manage sensitive cases, and continuously improve operational systems and policies.

Lead data science for Trainline’s B2B product organization by uncovering growth opportunities, shaping product roadmaps, defining success metrics, supporting experimentation, and driving data-informed decisions. The role requires communicating complex analyses to senior stakeholders, evaluating product engagement, navigating ambiguous datasets, building predictive models, and using visualization and automation tools to deliver measurable business impact.

Develop, validate, and deploy computer vision and machine learning algorithms for clinical decision support using imaging and sensor data. Own projects from messy data and modeling through rigorous evaluation and production integration. Collaborate with hardware, software, medical, and clinical research teams, apply classical and deep learning methods, support regulatory readiness, deliver production-quality Python code, and mentor colleagues.

Design and implement generative and predictive models of cellular behavior using biological and single-cell perturbation data. Develop models for generalization, counterfactual prediction, causal reasoning, and experimental design. Collaborate with experimental biology teams to validate computational hypotheses, evaluate mechanistic fidelity, and guide real-world interventions. Communicate findings across interdisciplinary teams while contributing to a matrixed, collaborative research environment.

Own and evolve the OneView product roadmap, prioritizing backlogs, defining requirements, resolving blockers, and guiding delivery. Translate customer, commercial, and company objectives into measurable product outcomes. Lead Scrum ceremonies, communicate priorities, manage dependencies, and use product evidence to adjust decisions. Establish scalable discovery and prioritization practices while supporting platform planning and cross-team coordination. The role is hybrid in London with occasional client travel.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

Develop and implement AI safety principles, policies, and operational processes for a mental health product. Investigate user reports and emerging risks, coordinate triage and escalation, translate findings into product improvements, and communicate safety practices internally and publicly. Collaborate with clinical, legal, engineering, research, and machine learning teams while handling sensitive information and making decisions under uncertainty.

Lead technical discovery, AI readiness assessments, solution design, demos, pilots, and proofs of value for Zendesk CX and employee service solutions. Architect secure, scalable integrations using APIs, middleware, telephony, and cloud platforms. Translate AI and automation capabilities into business outcomes, guide technical strategy throughout the sales cycle, demonstrate ROI, support AI adoption, and collaborate cross-functionally on product and go-to-market strategy.

Lead Ofcom’s technical strategy for AI and machine learning in online safety. Assess AI systems for safety, fairness, robustness, transparency, and accountability; shape AI governance and assurance approaches; lead research and complex technical programmes; advise senior leaders; engage external stakeholders; and build organisational capability through mentoring, knowledge sharing, and multidisciplinary leadership.

Legal Counsel will advise Quince’s UK and EU operations across commercial contracts, employment, privacy, consumer protection, AI governance, technology, logistics, product compliance, intellectual property, and risk. The role independently owns legal matters, builds processes and playbooks, supports international expansion, manages external counsel, monitors regulatory developments, and provides pragmatic guidance to cross-functional teams in a fast-growing technology-led retail business.

Lead marketing analytics and end-to-end measurement across growth marketing, including dashboards, pipeline attribution, ROI, CAC, LTV, forecasting, experimentation, and budget analysis. Partner with Marketing, Finance, RevOps, and Business Intelligence teams to connect spend to revenue, improve data quality, evolve attribution models, and automate reporting with AI and predictive modeling.

Develop and improve machine learning products for pricing, recommendations, and other business areas. Translate ambiguous business problems into practical models, experiments, and evaluations; collaborate with engineering, product, and analytics teams to deploy and monitor production models; investigate performance changes; and communicate insights to support evidence-based commercial decisions.

Own the market strategy and growth of Luma’s lab automation and orchestration solutions. Engage pharma, biotech, CDMO, and research customers; define segments, personas, positioning, competitive strategy, pricing inputs, and AI use cases. Enable global sales and marketing teams with messaging and sales tools, align Siemens organizations, support strategic pursuits, and build partnerships with automation vendors and thought leaders. Drive software adoption, pipeline growth, and customer movement toward connected and autonomous laboratories.

Build and operate scalable ML platform infrastructure supporting batch and real-time model workloads. Responsibilities include model deployment, serving, lifecycle automation, monitoring, observability, incident response, documentation, and collaboration with data scientists and engineering teams. The role also contributes to platform architecture, data products, reliability, technical standards, and data warehouse initiatives.

Lead analytical data science for Wise’s customer support organization. Measure service quality, diagnose root causes, design metrics, evaluate interventions, and use experiments, causal inference, machine learning, NLP, and LLM techniques to improve customer outcomes. Partner with Product, Design, Operations, and Engineering to guide automation strategy, prioritize opportunities, and influence product and business decisions using customer, conversational, and operational data.

Owns the UK Defence territory, selling Snowflake’s AI Data Cloud to the Ministry of Defence, defence primes, system integrators, and allied national security organizations. Responsibilities include prospecting, consultative enterprise sales, navigating public-sector procurement, aligning data and AI solutions to mission priorities, managing complex sales cycles, forecasting pipeline, and building relationships with mission owners and procurement stakeholders. The role requires UK Defence sales experience and the ability to hold or obtain UK security clearance.

Lead complex AI strategy and transformation engagements from diagnostic and use-case prioritization through production, adoption, and value realization. Manage multidisciplinary teams, client relationships, engagement economics, vendors, and senior stakeholder communications. Develop business cases, roadmaps, proposals, and thought leadership while translating business needs into technology-enabled solutions. Coach junior colleagues and support business development. Apply strong analytical, commercial, governance, and responsible AI judgment across enterprise transformation programs.

Supports technology, data, automation, and AI audits by assessing governance, controls, model risks, cybersecurity, data quality, and regulatory compliance. Designs analytics, automated testing, dashboards, and AI-enabled tools to improve continuous assurance and audit efficiency. Partners with technology and data teams, translates technical risks into business conclusions, advises auditors, and contributes to internal audit innovation and technology roadmaps.

Own the strategy and roadmap for AI-powered fraud investigation automation. Lead discovery, prioritization, production rollout, evaluation, governance, monitoring, and continuous improvement. Partner with Engineering, Data Science, Design, Operations, Risk, and Compliance to combine deterministic logic, machine learning, GenAI, human oversight, and operational processes into scalable, safe, compliant fraud solutions.

Develop and manage systematic trading strategies across global energy markets. Generate signals using fundamental market data, weather, supply and demand dynamics, physical flows, and alternative datasets. Build predictive models, design new signals, and improve portfolio construction, risk allocation, and execution. Manage the full research lifecycle from idea generation through live deployment and monitoring while collaborating with quantitative researchers, engineers, and data specialists.

Design and develop scalable full-stack software, data ecosystems, interactive drug discovery tools, and AI-enabled platforms for scientific research. Lead cloud-native architecture using microservices and event-driven patterns, integrate scientific data and computational workflows, establish engineering excellence across the SDLC, collaborate with research scientists, and mentor developers. The role requires deep backend, frontend, data engineering, cloud, and AI-assisted development expertise.

Build and improve the Perch camera system across platform, perception, and ML systems. Design tracking, segmentation, and motion-recognition algorithms; train and deploy ML models to edge devices; develop reliable customer-facing services; analyze production data; and optimize inference performance. The role requires hands-on Python and C++ development, strong backend engineering, distributed or data-intensive systems experience, and exposure to computer vision, ML infrastructure, signal processing, or real-time systems.

Designs mobile, desktop, and wall-display applications for healthcare and care staff. The role involves simplifying health data, creating workflows for different user levels, collaborating with AI and engineering teams, conducting customer site visits, prototyping in code, and designing around sensor and model limitations. Candidates should have 4+ years of software product design experience, strong information architecture skills, and ideally React or front-end development experience.