Top Machine Learning Jobs in London

As a Product Manager, you will lead the lifecycle of real-time payments fraud prevention products, translating client needs into product specifications, and collaborating with ML experts and regional teams for successful implementation.

As a Staff Machine Learning Engineer, you will enhance AV simulations using foundation models, lead experiments, develop realism metrics, and manage teams.

As a Senior Machine Learning Engineer, you will develop ultra-realistic simulations for autonomous vehicles using foundation models, collaborate with teams, design experiments, and integrate models into applications.

Work with sales and partners to present Snowflake to technical and executive stakeholders; run demos, proofs-of-concept, and designs; build technical champions; stay current on Snowflake roadmap and competing technologies; collaborate with product, engineering, partners, and sales to drive deals and customer success.

Design, build and operate production-grade, scalable full-stack systems for the consumer journey. Write well-tested code, improve production systems, collaborate with product and non-technical teams, and learn best practices around scalability, performance, and system design.

Join as a graduate quantitative researcher to design, build, test and deploy statistical and machine learning models for pricing, forecasting and signal discovery using large-scale market and unstructured data. Collaborate with researchers, traders and engineers to monitor production models, refine assumptions, and accelerate research-to-production using AI-enabled workflows.

Lead Boltz's enterprise sales, converting inbound interest into $1M+ ACV platform contracts. Drive high-value deals, scope complex engagements, negotiate contracts, expand accounts, and build a repeatable enterprise sales motion while partnering with CEO, science, and product teams.

Lead global go-to-market strategy for the IFS Sustainability portfolio: create repeatable GTM motions, develop sales plays, drive pipeline growth, support strategic deals, align Sales/Marketing/Product/Customer Success/Partners, and measure commercial performance to increase adoption and win rates.

Own and execute global go-to-market strategy for the Optimisation portfolio (PSO, MSO, WISE). Define proposition, build sales plays, drive pipeline generation and strategic deal support, and align Product, Sales, Marketing, Customer Success and Partners to grow revenue and adoption.

Work on live private equity, M&A and financing transactions: review, draft, and negotiate NDAs and ancillary documents using client playbooks; manage document queues and turnaround times; supervise and train junior team members; support live deal execution across concurrent transactions; collaborate with global legal, product, and engineering teams to improve AI-enabled workflows and internal processes.

Design, build, and operate reliable, scalable AI/ML platform infrastructure. Develop observability, resilience, security, and automation tooling, own NFRs, participate in on-call rotations, troubleshoot production issues, and collaborate cross-functionally to support large-scale AI deployments.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

Lead technical strategy and architecture for personalization, designing scalable systems for personalization, search, recommendations and ML features. Partner with Product, Data Science, and Design, influence cross-team technical decisions, mentor senior engineers, and improve engineering quality, reliability and productivity through tooling and best practices.

Lead long-cycle, consultative enterprise engagements with C-suite stakeholders to drive AI adoption. Build business cases, design pilots, advance opportunities to close, and partner cross-functionally to shape go-to-market strategy and scale commercial motion for Fortune 500 clients.

Own strategic client relationships and deploy Valence's generative-AI coaching across Fortune 500 accounts. Drive adoption, renewals, expansion, and measurable behavior change while partnering with Sales, Ops, and Product to shape roadmap and ensure successful implementations.

Lead design, development, and verification of autonomy solutions for defense: write perception and planning algorithms, prototype and deploy ML models, optimize performance, build system architectures, collaborate cross-functionally, mentor junior engineers, and test/debug with attention to documentation and emerging AI techniques.

The Computational Protein Design Scientist will leverage computational tools and AI to design proteins, collaborating with experimental teams and improving data-driven insights in synthetic biology.

Lead development of advanced analytics and machine learning models, create algorithms from scratch, analyze large datasets and relational databases, interpret results and recommend solutions, act as domain expert, perform manual claim selection and audit review, and generate new selection concepts/queries. May lead and manage a team.

Design, develop, and maintain Entrust's iOS SDK for document capture. Implement camera capabilities, on-device image processing and ML, integrate RESTful APIs, improve CI/CD and test automation, collaborate with product and design to deliver accessible, high-quality SDK features across devices.

Lead the Therabody mobile app roadmap and deliver cross-functional features that integrate software, firmware, hardware, and AI. Drive end-to-end execution from strategy and user research to engineering delivery, A/B testing, analytics, and go-to-market launch while partnering with design, marketing, and product development to improve engagement and conversion.

Lead pre-sales for managed services: capture client needs, design AI/cloud-managed service solutions, develop proposals, pricing and contracts, pitch and close deals, create reusable assets, and mentor teams.

As a Forward Deployed Engineer, you will design, develop, and deploy AI solutions, focusing on agent-based architectures, automation, and customer collaboration to enhance IT operations.

The Senior Applied Scientist will lead research projects in AI/ML for various legal and taxation solutions, focusing on developing scalable AI capabilities while mentoring junior team members.

As a Staff Machine Learning Engineer, you will build ML systems for content understanding, develop classification models, and improve content quality through collaborative work with various teams.

The Staff Machine Learning Engineer builds and scales ML systems for content detection and policy enforcement, collaborating with various teams to ensure safety and compliance in Spotify's user experiences.