Top Machine Learning Jobs in London

The role involves developing and optimizing machine learning models and collaborating on research projects with quantitative researchers.

The role involves developing an ML research and deployment pipeline, implementing best practices in model and feature management, and ensuring robustness in production through effective solutions and collaboration.

Conduct research using machine learning techniques to develop investment strategies, leveraging extensive data and computational resources.

The role involves developing machine learning models, optimising system performance, and collaborating with diverse teams on innovative projects.

Lead design, deployment, and iteration of large-scale ranking models (recommendations and search). Collaborate cross-functionally, manage end-to-end ML lifecycle, drive research and innovation, and mentor team members while delivering measurable product outcomes.

The Senior ML Infrastructure Engineer will manage and optimize the ML infrastructure, focusing on training pipelines, model serving, and collaboration with research teams.

Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.

As a Research Engineer, you will develop and optimize AI models for drug discovery, collaborating with scientists to advance ML applications in biopharmaceuticals.

As an AI Research Engineer at Helsing, you'll architect and enhance deep learning frameworks, optimize infrastructure for distributed training, and develop strategies for large datasets while collaborating with a cross-functional team.

The role involves developing, fine-tuning, and optimizing large language models, building ML infrastructure, and implementing CI/CD practices for AI/ML systems.

The Senior Customer Success Manager will build strategic client relationships, ensure product adoption, lead onboarding, provide technical support, and drive operational improvements within the company.

The New Business Development Manager will drive business growth in the commercial real estate sector, manage sales cycles, and support operational excellence.

Lead a pod of data scientists (25%) while spending most time (75%) developing, validating, and deploying ML algorithms from sensor and imaging data for clinical decision support. Drive technical standards, production-quality code, cross-functional validation with engineers and clinicians, and contribute to Data Science leadership and regulatory readiness.

Lead and grow engineering teams building a broker platform. Drive technical strategy, deliver microservice-based features, advocate Agile/Lean practices, recruit talent, measure team impact, and collaborate with senior stakeholders and CTO on architecture and infrastructure.

Lead and grow a team of ML engineers to build and operate production ML and LLM systems—real-time inference APIs, batch data products, and agentic AI—ensuring deployment, monitoring, CI/CD, reproducibility, and measurable business impact.

Lead development of enterprise commercial intelligence: build data models (pipeline, forecasting, segmentation), deploy AI/ML for forecasting and churn, create dashboards, establish data governance, partner with senior leaders to drive insight-led decisions and adoption across global teams.

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

Lead statistical planning and delivery for clinical studies using R and RShiny, mentor biostatistics staff, prepare SAPs and programming specifications, perform quality control, support submissions and regulatory interactions, and develop/maintain R-based visualization apps and infrastructure.

Lead the design, development, and operation of analytical and ML systems for financial services, ensuring model accuracy and compliance.

Lead and scale a regional Market & Customer Intelligence program across EurAsia, turning market and customer insights into actionable, AI-enabled analytics and decision-ready narratives. Own rollout roadmaps, governance, intelligence cycles, stakeholder enablement, KPI tracking, and cross-functional adoption to embed the capability as a trusted enterprise asset.

Lead integration of a counter-UAS initiative combining robotics, ML, and systems engineering. Build prototypes, run trials, and implement sensor fusion, vision models, state estimation, and hardware/software integration alongside product and external partners.

Design, build and deploy production-grade ML systems for retail and consumer clients. Lead technical scoping, architecture and best practices, collaborate with data scientists and engineers, operationalise models, and advise customers to deliver scalable, secure ML solutions that drive business outcomes.

Lead enterprise sales for Everpure's AI/HPC data infrastructure, driving large deals with F1000 companies. Build executive relationships, lead cross-functional pursuit teams, influence product roadmap, manage a pipeline to exceed revenue targets, and evangelize all-flash storage and data pipeline solutions for AI workloads.

Surgo Health seeks a Senior Product Manager for AI and Data Products to define product strategy, lead product initiatives, and collaborate with cross-functional teams. The role emphasizes building AI-driven solutions in healthcare and requires strong product management skills with a technical background.

Lead the Domain Platform Engineering and AI team to rebuild an enterprise data platform, driving innovation, aligning technical roadmaps, and improving engineering practices while fostering a high-performance culture.