Top AI Engineer Jobs in London

As the first hire, you will design AI systems for drug development, bridge pharma strategy and engineering, and translate client needs into product features.

Lead the technical development of a platform automating legal workflows for venture capital, designing and building core systems, and integrating AI for document processing.

The Staff Engineer will lead the development of technical infrastructure, manage AWS cloud operations, design database systems, and build production APIs. This role requires strong expertise in distributed systems and data pipelines.

Lead the full lifecycle of AI development, drive innovation from research to deployment, design scalable AI systems with Python, and overcome complex challenges in real estate.

The Senior Full-Stack Product Engineer will develop features for an AI anti-financial crime platform, building back-end systems and front-end interfaces while optimizing AI models and automation systems.

Lead the development of AI features, drive product strategy, and optimize infrastructure for growth without PM interference, owning core product areas.

Architect and build backend systems managing billions of data points, ensuring high performance for machine learning workflows, and scaling infrastructure during hyper-growth.

As the first technical hire, you'll build end-to-end product features, integrate AI models, and enhance application performance.

As a Staff Software Engineer, you will develop user-facing features, focus on performance and usability, and collaborate with designers and product managers on high-quality code, owning features end-to-end.

Lead the development of AI-driven solutions, architect scalable AI products, mentor junior engineers, and integrate AI across the organization.

As an AI Research Engineer focused on AI Safety, you will develop techniques for evaluating AI products, enhance decision-making via uncertainty quantification, and ensure robustness against adversarial attacks.

As an AI Developer, you'll design AI-driven document features, integrate capabilities into tools, optimize performance, and engage in systems design and coding across languages.

As a Senior Python Backend Engineer at VidRush, you'll build AI-driven video production systems, ship production-level ML/LLM services, and work closely with product teams while ensuring high autonomy and delivery speed.

This role involves designing, building, and operating AI-ready cloud platforms, focusing on public cloud infrastructure and AI service delivery in a regulated environment.

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.

As the first full-time engineer, you'll transform a prototype into a SaaS by developing backends, designing user interfaces, and implementing security standards.

The AI Infrastructure Engineer will build and optimize training pipelines and inference services for AI models, enhance GPU-level performance, and mentor team members.

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.

Lead and mentor a team of AI/ML Engineers, developing production-grade AI solutions that extract value from structured and unstructured data, with a focus on customer-centric performance.

As an AI Solutions Engineer, you'll design AI solutions, run technical discovery, and guide customers on integrations and workflows to drive value with V7 Go.

The Software Engineer will shape AI governance in developer tooling, build product features, collaborate with teams, support users, and innovate rapidly.

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

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

The Staff Product Engineer will build AI-powered products, collaborate with ML scientists, contribute to software development phases, and mentor other engineers.