Top AI Jobs in London

The Staff AI Engineer will lead the technical direction for a platform managing financial service agents, tackling complex AI challenges and ensuring policy compliance.

Design, build, and deploy machine learning models and intelligent data systems for Formula 1, focusing on predictive analytics, computer vision, and natural language processing, while collaborating across teams to identify data opportunities.

Join a pioneering team in post-quantum cryptography, working on RISC-V based security solutions. Collaborate on innovative technologies in a flexible environment.

Lead the development of AI models for drug discovery, optimize performance, collaborate across teams, and drive innovation in healthcare.

Join Watershed's sustainability AI reporting team to prototype, build, and productionize AI features (LLMs, embeddings) for information extraction and report generation. Ship production-ready, well-tested full-stack code and keep systems current with state-of-the-art AI to deliver customer-facing product features.

Own outbound and inbound pipeline for AI cloud users, manage outreach automations, re-engage sign-ups, coordinate discovery and partner calls, maintain CRM hygiene, attend events, and design GTM experiments with founders and CRO.

The AI Engineer - FDE role involves developing and deploying GenAI applications, collaborating with cross-functional teams, and advising customers while presenting thought leadership in the field.

Drive technical pre-sales for Databricks AI/BI product line: design engagement strategies, deliver demos/workshops, advise on lakehouse analytics, resolve tier-3 technical issues, and influence product roadmap to increase adoption and customer success.

Design, implement, and optimize AI/LLM workflows and infrastructure. Collaborate across teams to integrate models into production, document best practices, and optimize performance and costs.

Design, build, and operate low-latency multi-agent LLM systems. Ensure high-quality real-time communication and optimize prompt programming and retrieval processes.

The Senior AI Engineer will design, build, and deploy AI-driven solutions, collaborating with teams to enhance products using Generative AI technologies.

Design, build, deploy and iterate LLM-based applications and generative AI solutions. Partner with product and business teams to optimise internal workflows, implement cloud-based end-to-end solutions, and ensure reliability, scalability, and observability.

Design end-to-end AI experiences for consumer and enterprise products: research opportunity areas, prototype agent behaviour/personality, craft UI/UX and brand-aligned visual expression, and work with engineering to build testable, trustworthy AI solutions.

Lead new logo acquisition across the US and UK, targeting large enterprise, HPC, and AI model/application builders. Own identification, pursuit, and negotiation of complex multi-year GPU cluster deals, maintain executive-level relationships, and align commercial contracts with Legal, Finance, and delivery teams.

As an AI Engineer, you'll enhance IT platforms by building secure AI orchestration systems, designing autonomous agents, and fostering AI fluency within the organization.

You will optimize algorithms, evaluate third-party technologies, and assume ownership of existing code while transitioning to a research-oriented role. A strong academic background in mathematics or engineering is required, with proven programming skills.

Design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data. Implement data storage and ingestion for ML workloads, enable BI and visualization tools, own features end-to-end, maintain CI/CD and observability, and collaborate with data scientists to ensure secure, reliable, performant systems.

Hunt new-logo enterprise accounts for Loops CX and OEM channels, build pipeline, lead consultative executive-level selling, close complex $500k+ ACV deals, manage opportunities in HubSpot, and partner with customer success to ensure deployment and adoption.

Provide methodological and statistical leadership across projects, design and deliver advanced analytics and ML solutions (including deep learning and NLP), mentor staff, manage client relationships, and drive business development in health outcomes and pharmaco-economics.

The Technical Lead will oversee the design, development, and implementation of AI-driven projects, collaborating across teams and managing technical strategy while being client-facing.

The Principal Test AI Engineer defines testing strategies for AI systems, leads validation efforts, architects automated testing frameworks, mentors engineers, and translates AI risks into insights for stakeholders.

The Principal AI Test Engineer will define AI testing strategies, lead validation for AI systems, architect automated test frameworks, and mentor engineers to enhance product quality and compliance.

Lead AI projects in Clinical Development for Life Sciences. Engage with clients, manage teams, design solutions, and shape a new practice.

The Associate Principal will lead AI-driven projects in Life Sciences, support business development, and ensure high-quality delivery while collaborating with various stakeholders.

The AI Enablement Manager will drive the adoption of AI tools across teams, optimize workflows and client success through innovative AI solutions.