Top Machine Learning Jobs in London

Leads complex AI and digital transformation programmes for UK Government and international public-sector clients. Responsibilities include overseeing portfolios spanning strategy, R&D, and product delivery; developing proposals and growing the public-sector business; advising senior customers on AI strategy and implementation; managing client relationships; mentoring teams; and ensuring high-quality outcomes. Requires public-services experience, GDS-style product delivery, AI and ML understanding, technical credibility, consulting delivery expertise, and strong leadership in ambiguous, high-stakes environments.

Eight-week quantitative investing internship at BlackRock for specialized master's students. Interns contribute to investment or client projects, support quantitative research and portfolio management, analyze large datasets, translate statistical models into Python, and learn about capital markets, economic theory, portfolio trading, and investment strategies. Opportunities span quantitative research, portfolio management, product strategy, and investment technology across systematic equity and fixed-income teams.

Leads product strategy execution for a domain, manages and develops Product Managers, drives portfolio prioritization and OKRs, and ensures measurable outcomes. Coaches teams on discovery, AI-first workflows, customer engagement, stakeholder alignment, and regulated GxP software development. Partners with strategy, engineering, sales, and customer-facing teams while maintaining product quality, regulatory readiness, and cohesive cross-domain execution.

Build reliable, well-tested platform software for AI-powered industrial control systems. Responsibilities include developing with Python and Terraform, supporting production systems, improving architecture, mentoring engineers, strengthening software practices across engineering and ML teams, and enhancing system quality, maintainability, and reliability. The role spans CI/CD, networking, plant-system data integration, IoT operating systems, and customer-facing control software.

Leads Gigaton’s Solutions team and owns deployment of AI systems across industrial customer plants. The role is responsible for scaling from 9 to 50 live plants, reducing deployment timelines, converting bespoke work into repeatable product capabilities, managing escalations, defining evaluation success, developing post-sales operations, and hiring and coaching a high-performing deployment organization. Requires customer leadership, hands-on deployment experience, and approximately 25% travel to global plants.

Own a portfolio of UK and European B2B customers, managing relationships, renewals, retention, account health, and expansion opportunities. Run QBRs, build senior stakeholder relationships, maintain Salesforce records and forecasts, and collaborate with Sales, Customer Success, Product, and Delivery teams. The role requires identifying customer risks and growth opportunities while helping customers apply workplace data and analytics to improve their environments.

Leads Yondr’s global cost estimating and benchmarking strategy for large-scale data center construction. Responsibilities include developing estimates from concept through construction documents, maintaining cost benchmarks, managing central estimating resources, analyzing project data, improving forecasting processes, supporting international projects, and presenting recommendations to senior leadership. The role partners with design, engineering, procurement, finance, and operations teams while exploring AI and machine learning to improve cost-efficiency and forecasting accuracy.

Lead customer-facing Zendesk implementation projects from discovery and solution design through configuration, onboarding, training, and adoption. Translate business requirements into scalable platform solutions, manage project scope, timelines, budgets, risks, and competing priorities, and communicate recommendations to technical and executive stakeholders. Collaborate with services, sales, product, and post-sales teams while maintaining product expertise across Zendesk Support, Messaging, Knowledge, Voice, Analytics, QA, Workforce Management, Copilot, and AI agents.

Develop statistical and machine learning sports models, engineer data assets, implement pricing engines in Python, and integrate solutions into Sportsbook applications. Build automated tests, validate data flows, support model deployment and lifecycle management, collaborate with Trading, Product, Engineering, and QA, and mentor junior data scientists.

Design user experiences for an agentic AI platform used by large organizations. Responsibilities include user research, UX/UI and interaction design, prototyping, user testing, A/B testing, impact measurement, roadmap shaping, and collaboration with product, engineering, and research teams. The role focuses on making complex AI workflows understandable, trustworthy, and intuitive while contributing to design systems and exploring code and AI-assisted design workflows.

Lead cross-functional Risk initiatives from strategy through delivery and adoption. Define product and technical direction for risk infrastructure, data, AI, APIs, and user experiences; partner with engineering, data science, ML, and executive leaders; make investment decisions; resolve complex tradeoffs; influence without authority; mentor PMs; and advance product management practices across Stripe.

Leads the identification, development, integration, and global deployment of AI and automation solutions for legal editorial, metadata, and content operations. The role supports AI strategy, evaluates designs against governance and quality standards, manages cross-functional projects, reports data-driven outcomes, tracks industry trends, documents improvements, and promotes responsible AI use.

Supports enterprise sales by discovering customer requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value engagements. Acts as a technical lead and consultative advisor, educating customers on architecture and best practices. Collaborates with sales, product, professional services, partners, and customer success teams while developing AI-driven and agentic solutions for demonstrations and customer outcomes.

Build and improve Firefox WebCompat internal dashboards, reporting tools, and broken-site screenshot capture pipelines. The role involves creating reliable data views for triage and metrics, automating screenshot workflows, collaborating with WebCompat and QA teams, and translating reporting needs into effective tooling. Familiarity with WebCompat workflows, Bugzilla, screenshot automation, and machine learning is preferred.

Provides actuarial pricing and analytics support for Bupa’s UK insurance products. Responsibilities include analyzing portfolio performance, developing pricing recommendations, building models, evaluating customer and competitor trends, supporting product changes, interpreting results, and preparing reports for senior stakeholders. The role involves data extraction and refinement, advanced analytical techniques, technical documentation, and collaboration with Sales, Finance, Product, Clinical Policy, and Healthcare Analytics teams.

Own the B2B sales pipeline and revenue for AI and data services. Responsibilities include outbound prospecting, qualifying technical buyers, managing complex pilots and recurring contracts, developing partnerships and channels, shaping pricing and commercial terms, protecting margins, and feeding customer demand into product and operations. The role requires experience selling AI/ML data, annotation, licensing, or related technical services to research and enterprise buyers.

Lead hands-on development of production-grade AI systems, including RAG pipelines, semantic search, embedding infrastructure, LLM orchestration, and integrations with legacy and multi-cloud environments. Establish engineering standards, mentor developers, implement responsible AI guardrails, and ensure secure, observable, reliable deployments. Support knowledge transfer to government engineers, promote sustainable AI practices, and work with multidisciplinary public-sector teams. The role is hybrid in Newcastle and requires weekly travel there, UK-only system and data access, and BPSS clearance.

Lead NVIDIA’s engagement with AI-native startups, scaleups, and labs. Understand customer needs, develop AI technology solutions, coordinate technical and business resources, drive adoption and partner growth, create customer references and case studies, identify emerging use cases, and represent NVIDIA at industry events.

Design and implement explainable AI/ML solutions, multi-agent systems, and production-grade data science tools for Risk Management and Compliance. Develop secure code, APIs, batch pipelines, monitoring, and retraining processes while partnering with Product, Engineering, Model Risk, Compliance, and business stakeholders. Support Responsible AI standards through documentation, fairness testing, human-in-the-loop controls, Agile delivery, and operational integration.

Develop and deploy production AI/ML applications for digital banking, using Python, SQL, cloud platforms, LLM patterns, classical machine learning, and data analysis. Responsibilities span requirements gathering, solution design, prototyping, evaluation, deployment support, monitoring, governance, and iteration. The role collaborates with product, operations, marketing, and technical teams to deliver customer and operational improvements while supporting risk, privacy, and model controls.

Manage NVIDIA’s relationships with AI-native startups, scaleups, and labs. Identify customer needs, develop AI solution strategies, drive adoption of NVIDIA platforms, coordinate cross-functional and partner resources, create customer references and case studies, develop emerging use cases, and represent NVIDIA at industry events. The role requires strategic market analysis, AI business development expertise, ecosystem relationships, and strong communication skills.

Owns strategy and growth for a defined market segment within CluePoints’ clinical-trial SaaS portfolio. Responsibilities include developing go-to-market strategies, coordinating product, marketing, sales, consulting, customer success, and finance teams, enabling teams to launch and support products, advising strategic customers, and leading user communities. Success is measured through market penetration, win rate, retention, NPS, and gross margin.

Own and build the company’s metadata-driven data layer as a hands-on principal architect. Design schema-flexible and versioned platforms with lineage, auditability, semantic mapping, and resilience to schema changes. Write production code, establish AI-assisted engineering practices with verification, coach engineers, and communicate architecture to technical and business stakeholders. Experience with regulated data, multi-tenant SaaS, semantic technologies, or clinical data standards is valuable.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Serve as a customer-facing fraud and identity expert across pre-sales, onboarding, and expansion. Design risk strategies and identity workflows, advise customers on fraud mitigation, coordinate technical and regulatory implementation requirements, validate milestones, and lead go-live readiness. Partner cross-functionally with Product, Engineering, Legal, and Compliance teams to accelerate deployment, adoption, and customer value.