Artificial Intelligence Jobs

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving experience. Own the loop end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

PyTorch · GAIA · GPU +1

• London
• Hybrid
• Mid-level
• Permanent

Develops embedded software connecting an AI Driver to vehicle steering, braking and propulsion systems, working hands-on with benches and vehicles. Involves MATLAB/Simulink development, drive-by-wire actuation logic, CAN/CAN-FD diagnostics, OTA updates and ADAS/HMI interfaces, collaborating with OEMs, suppliers and controls engineers.

MATLAB · Simulink · CANoe +6

• London
• Hybrid
• Senior
• Permanent

Builds and operates the platform running long-lived agentic workflows, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, weighted towards backend and platform in TypeScript and Node.js.

Restate · PostgreSQL · Google Cloud +7

• London
• Hybrid
• Senior
• Permanent

Builds and operates the platform running long-lived agentic workflows in production, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, with a backend and platform weighting in TypeScript and Node.js.

Restate · PostgreSQL · Google Cloud +7

• London
• Mid-level
• Permanent

Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training workloads, identifying slow or faulty nodes and surfacing performance bottlenecks. Work deep in the stack across collective communication, parallelism, fault tolerance, and observability, collaborating with systems, infrastructure, and research teams to evolve the training platform.

• London
• Senior
• Permanent

Builds and operates shared multi-cloud compute platforms behind ChatGPT and the OpenAI API, spanning Kubernetes cluster lifecycle, upgrades, patching, capacity management, autoscaling and infrastructure automation. The role carries end-to-end production ownership, including on-call incident response, and focuses on reusable platform tooling across OCI, AWS and Azure rather than GPU optimization.

Kubernetes · AWS · Azure +2

• United States
• Hybrid · 3 days in office
• US$200,000 – US$225,000 pa
• Mid-level

Build and own core platform capabilities including application infrastructure, APIs and shared services, developing full stack applications in Python, React and TypeScript. Surface machine learning and predictive analytics insights through intuitive interfaces and integrate AI/LLM workflows into production, working in a small innovation team with significant architectural ownership.

Python · React · TypeScript +1

• Salford
• Hybrid
• Mid-level

Builds production-grade generative AI solutions using Python, OpenAI and Anthropic LLMs, REST APIs and agentic technologies within a cross-functional engineering team. Offers freedom to experiment with emerging AI tooling such as Amazon Bedrock and LiteLLM, taking applications from proof of concept through to production.

OpenAI · Anthropic · GitHub Copilot +5

• Southampton
• £75,000 pa

Build cloud applications, customer portals, APIs and integrations that turn complex data into useful products, while developing AI capabilities such as document intelligence, semantic search, RAG and intelligent agents. Use tools like Claude Code and Codex to accelerate development, modernise platforms and shape architecture and engineering practices alongside domain specialists.

Claude Code · Codex · Azure +2

• London
• Hybrid · 3 days in office
• Mid-level

Join a newly formed Scheduling team to own and extend systems that orchestrate compute allocation for complex ML workloads on Kubernetes. You'll design scheduling policies like gang scheduling and topology-aware placement, build custom Kubernetes controllers and CRDs, and partner with ML researchers to maximize GPU/TPU utilization.

Kubernetes · Kueue · Volcano +5

• Hatfield
• Hybrid
• Entry level
• Temporary

Two-year rotational graduate scheme with four six-month placements across areas such as bot software and hardware, eCommerce, fulfilment and data. Graduates work in teams on robotics, low-latency control systems, ML and warehouse simulation, building a broad view of the business before moving into a long-term role.

Ocado Smart Platform

• Cambridge
• £35,000 – £45,000 pa
• Entry level

Engineer the future of defence and securityThis team is motivated by saving lives in war affected regions and on the battlefield. They believe that by combining advanced technologies from different sectors they can fundamentally change the effectiveness of those we…

• London
• £90,000 – £110,000 pa
• Senior

Design and optimise multi-threaded C++ pipelines for image processing, computer vision and rendering, tuning algorithms for spatial analysis, sensor alignment and scene reconstruction. Work with GPU acceleration and parallel computing to hit strict performance targets, influence architecture and review code, plus take a turn on the production support rota.

C++17 · Git · CMake +5

• Gloucestershire
• Hybrid
• £51,000 – £60,500 pa
• Senior

Works across multiple projects and all stages of the SDLC, leading software design, development, testing and deployment for AI and Computer Vision products. Splits time between internally and externally funded R&D, product development and client-facing service work, providing SME guidance on architecture and design within multidisciplinary teams.

Red Hat · Ubuntu · Pandas +6

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining cloud infrastructure across research, development and production. Work spans GCP, Kubernetes, Docker, Terraform and Kapitan, plus CI/CD, observability and tooling, partnering with scientists, ML researchers and product teams. Reports to the Director of Engineering in a small, fast-moving team.

GCP · Kubernetes · Docker +7