Top Machine Learning Jobs in London

Lead technical direction and delivery of complex ML projects: design and operate scalable ML systems, define roadmaps, build reusable libraries, mentor engineers, hire, and advise clients on architecture and estimates to deliver safe, production-grade AI solutions.

Build, deploy and productionise ML systems and infrastructure; design scalable, reusable ML solutions; lead technical scoping and architecture; collaborate with engineers, data scientists and clients; act as technical advisor to stakeholders.

As a Graduate Machine Learning Researcher, you will design, test, and implement machine learning models to enhance predictive analytics for sports betting. The role demands creativity and a solid understanding of Machine Learning principles and core statistics, working closely with a quantitative modeling team.

The Senior Platform Engineer in Machine Learning at Monzo will design, maintain infrastructure for ML models, and work with various cloud technologies.

Design and implement ML and graph-ML solutions to analyze, extract, and generate knowledge from heterogeneous biomedical data. Enrich and reason over a biological knowledge graph using classification, relationship discovery, RAG/LLM techniques, and production-ready models. Collaborate cross-functionally to architect, train, deploy, and monitor scalable ML systems and provide technical leadership on Knowledge Enrichment projects.

Develop data and analytics products using machine learning and MLOps, build scalable language services, and automate testing and deployment in a SaaS environment.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Lead Machine Learning Engineer, you'll set technical directions for AI projects, design scalable ML systems, lead project delivery, and mentor a team of engineers while collaborating with clients to achieve their goals.

As a Machine Learning Engineer, you will design, build, and deploy ML systems, manage AI project methodologies, and support delivery with technical expertise, collaborating with cross-functional teams and stakeholders.

As a Principal Java Engineer II in the ML Core team, you will build and maintain machine learning components for Elasticsearch, collaborate with engineering teams, and ensure scalable and high-quality code. You'll lead projects from design to implementation while supporting the team and community.

Lead the development and deployment of AI systems, designing scalable ML software and infrastructure while mentoring junior engineers and advising clients.

The Senior Data Engineer designs, maintains, and optimizes ML applications and data pipelines, ensuring compliance and quality while mentoring junior engineers.

As a Senior Data Engineer, you will design and maintain ML applications, manage workflows, build data pipelines, and mentor junior engineers within a global team.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.