Top Machine Learning Jobs in London

Leads the strategy, commercial modeling, acquisition, and scaling of ExtraHop’s MSSP and MDR business across EMEA. Owns partner pipeline, recurring revenue, executive relationships, co-selling, and sell-through motions. Builds commercial frameworks, enables MSSP technical teams, provides product feedback, and initially operates as a player-coach before recruiting and managing account managers and channel solutions architects.

Leads the demand generation engine, translating go-to-market priorities into segmented campaigns across email, search, social, content, webinars, and events. Owns marketing automation, lead scoring, Salesforce integration, pipeline reporting, conversion metrics, budgets, and agency performance. Partners with Sales and Commercial Operations to improve handoffs and qualified opportunities, applies AI and automation to campaign execution, and recruits and coaches future demand generation team members.

Own the strategy, roadmap, and lifecycle of Cloudflare’s enterprise Email Security platform. Lead threat detection investments, Zero Trust integration, customer discovery, competitive differentiation, and global launches. Partner with engineering, threat intelligence, sales, and design teams to address email threats such as business email compromise and phishing. Drive product growth, enterprise adoption, and technical platform evangelism while making data-informed investment decisions.

Lead technical development of production-grade computer vision and machine learning systems for video-based action recognition in retail. Responsibilities include designing end-to-end video ML pipelines, defining experiments, training and evaluating models, optimizing precision, recall, and latency, managing annotation workflows, and deploying privacy-aware solutions. The role also involves technical leadership, roadmap development, cross-functional collaboration, and translating ambiguous product challenges into robust commercial prototypes.

Leads data analytics for Internal Audit by extracting, transforming, analyzing, and visualizing data to assess risks and controls. Develops dashboards, management information, automation, and advanced analytics using SQL, Python/R, Power BI, AI, and machine learning. Supports data governance, quality, metadata management, audit process improvement, and stakeholder communication while maintaining audit methodology and professional standards.

Lead the modernization of trading operations through AI, machine learning, and automation. Manage trade lifecycles, P&L attribution, reconciliations, data integrity, risk monitoring, and performance reporting across multi-asset trading activities. Build agentic AI workflows, predictive risk models, anomaly detection tools, automated commentary, and real-time dashboards using Python, SQL, LLMs, and MLOps technologies.

Leads high-impact AI and data science projects for retail and consumer clients. Defines technical approaches, translates business problems into scalable solutions, designs software architectures, manages delivery timelines, builds client relationships, mentors data scientists, and promotes responsible AI practices. The role also contributes to business development, hiring, project scoping, and the development of production-grade machine learning and agentic AI systems.

Leads technology and IT internal audits across an algorithmic insurance carrier and Lloyd’s syndicate. Assesses risk management, control design, operating effectiveness, cybersecurity, data governance, software development, cloud, machine learning, underwriting, and insurance processes. Plans audits, performs fieldwork and testing, documents evidence, negotiates findings, produces reports, monitors remediation, supports Audit Committee and Board reporting, and advances audit methods through data analytics and AI tools.

Manage and mentor Data Scientists while overseeing the full lifecycle of machine learning models used for real-time payment decisions. Shape the Payment Intelligence roadmap, guide production-grade model development on GCP and Vertex AI, collaborate with engineering, product, and design teams, and communicate ML strategy and business value to senior leadership. The role focuses on fraud prevention, payment optimization, and scalable fintech innovation.

Supports EMEA data governance and risk management across asset and wealth management. Responsibilities include maintaining governance standards, coordinating forums, investigating policy breaches, tracking remediation, supporting data protection activities, improving processes, managing workstreams, reporting metrics, and coordinating regulatory requirements. The role partners with Risk, Compliance, Legal, Audit, Technology, data owners, and senior stakeholders while identifying opportunities to use AI and automation.

Lead the transformation of legacy products into a unified enterprise platform. Translate strategy into roadmaps, manage backlogs, prioritize cross-functional initiatives, and coordinate Engineering, UX, AI, Data Science, Commercial, and Operations teams. Drive platform discovery, delivery, launch, adoption, and measurable business outcomes. Integrate trustworthy AI and data capabilities into customer-facing workflows while influencing senior stakeholders and balancing customer value, commercial goals, technical feasibility, risk, and resources.

Leads the development and delivery of operational excellence and process improvement consulting services for financial services clients. Responsibilities include developing go-to-market strategies, building sales pipelines, creating intellectual property, supporting proposals, winning engagements, and overseeing transformation programs. The role requires expertise in process optimization, Lean methodologies, automation, digitization, operational risk, customer journeys, data governance, technology modernization, resilience, and workforce transformation, along with strong commercial and engagement leadership skills.

Supports public-markets investment research, portfolio construction, monitoring, and continuous improvement across multi-asset, systematic, and fundamental equity portfolios. Develops quantitative models, analytical tools, datasets, dashboards, and reporting using Python and financial data. Partners with portfolio managers and cross-functional teams to analyze performance, risk, exposures, and investment opportunities while strengthening research and technology infrastructure.

Lead the design, implementation, and delivery of software components supporting machine learning inference on PlayStation consoles. Provide hands-on technical leadership for GPU inference systems, define architectures and project scope, establish technology strategies, and collaborate with global internal teams, hardware and software stakeholders, external vendors, and game developers.

Lead the research, development, testing, deployment, and maintenance of complex machine learning and generative AI models. Design MLOps pipelines for CI/CD, monitoring, retraining, and production operations. Solve complex technical problems, evaluate emerging AI technologies, deliver high-risk prototypes, integrate models with existing systems, and ensure model safety, security, performance, and reliability. Mentor junior team members and provide specialist generative AI expertise for public sector and national security projects.

Lead research, design, and evaluation of large-scale detection models for automated, fraudulent, and malicious activity. Define measurement frameworks for noisy or incomplete ground truth, mentor data science practitioners, advance AI/ML techniques, and shape long-term detection strategy. Partner with ML Engineering, Data Engineering, and Product teams to influence roadmaps and protect Cloudflare customers from evolving threats.

Principal Product Manager leading the strategy, roadmap, and evolution of Unity LevelPlay’s mobile advertising mediation platform. The role owns platform decisions across auctions, bidding, network integrations, monetization, analytics, and publisher tooling. Responsibilities include partnering with engineering, data science, design, publishers, and ad networks; driving revenue-impacting decisions; aligning stakeholders; shipping scalable products; and mentoring other product managers. Deep ad tech, marketplace, mobile gaming, experimentation, and machine learning experience is expected.

Lead the design, development, optimization, and production deployment of machine learning and statistical models for automated insurance risk assessment and underwriting. Architect scalable data pipelines and infrastructure, collaborate with data scientists, engineers, and underwriters, mentor engineers, establish technical best practices, and evaluate emerging AI and machine learning techniques.

Leads a cross-functional engineering team building machine learning and AI-powered payment intelligence products. Owns product quality, delivery, operations, technical standards, prioritization, experimentation, and stakeholder expectations. Manages engineers, supports hiring and career development, and collaborates with product managers, designers, data scientists, and commercial teams. Contributes technical expertise across backend and frontend development while fostering reliable, well-tested systems and a strong culture of experimentation.

Manage workstreams for bespoke AI transformation projects with pharmaceutical and life sciences clients. Responsibilities include understanding stakeholder needs, conducting open-source analysis, translating operational requirements into user stories, designing and testing workflows, collaborating with engineering teams, and contributing to thought leadership. The role requires prior technical transformation consulting experience, life sciences exposure, client relationship skills, analytical communication, and familiarity with Agile and iterative delivery.

Responsible for the roadmap of a technical product, collaborating with engineers and stakeholders to develop, launch, and grow products.

Lead and coach a team of 10+ senior and Staff machine learning engineers focused on audio, video, and text content understanding. Set technical strategy, guide modeling and retrieval decisions, deliver high-priority cross-functional initiatives, and contribute hands-on as needed. Shape long-term audio understanding expertise, promote practical AI use in engineering workflows, and partner with product, design, research, and engineering leaders.

Lead the vision, strategy, roadmap, and lifecycle of data, analytics, and AI-enabled products. Identify commercial opportunities, develop pricing and business cases, manage budgets, and drive product profitability. Partner with Product, Data Science, Engineering, and Commercial teams to deliver scalable solutions. Lead and develop Data Product Managers while influencing senior stakeholders and translating technical capabilities into customer and business value.

Leads the design, productionization, and operation of LLM-powered agentic commerce applications. Builds retrieval systems, agent memory, organizational context, multi-agent workflows, evaluation frameworks, guardrails, and ML pipelines. Deploys resilient, observable solutions on AWS or Azure using MLOps practices, while partnering with product, business, data science, and engineering stakeholders to deliver secure, auditable production agents.

Forward Deployed Engineers embed with strategic clients to design and deliver production-grade technical solutions. Responsibilities include building Python applications, complex SQL queries, data pipelines, API integrations, cloud and data-platform solutions, and AI/ML prototypes. They lead technical discovery, architecture, implementation, debugging, workshops, and operationalization while translating client mission needs into scalable product improvements. The role requires strong communication, ambiguity management, and up to 50% travel.