Artificial Intelligence Jobs

• London
• Hybrid
• Lead
• Permanent

Own end-to-end system architecture for the Wayve AI Driver across L0–L4, defining interface contracts, sensor and compute topology, redundancy and safety mechanisms. Lead technical alignment with OEMs, Tier 1s and partners, and support integration, bring-up and system-level debugging on vehicles and HiL/ViL benches.

Linux · RTOS · HiL +3

• London
• Hybrid
• £255,000 – £325,000 pa
• Senior

Product engineer building internal tools and platforms at the intersection of engineering, product, and design. You'll design, prototype, and ship full-stack features in Python, TypeScript, and React, working directly with users to spot patterns and build reusable primitives rather than one-off features.

Python · TypeScript · React

• London
• Hybrid
• Senior
• Permanent

Owns embedded software that connects an autonomous driving AI to vehicle platforms and onboard systems, spanning inference integration, vehicle data, navigation, localisation, odometry and motion control interfaces. Works in C++ on Linux/QNX across Nvidia and Qualcomm hardware, taking features from design through HIL and vehicle testing, and shaping architecture reused across vehicle programmes.

Nvidia · Qualcomm · Linux +3

• London
• Hybrid
• £325,000 – £395,000 pa
• Senior

Builds foundational infrastructure for AI safety safeguards, including data storage, metric and evaluation systems, and tooling for human and agentic review. Maintains real-time, multi-layered defenses against misuse at scale while reducing manual oversight, working across the stack primarily in Python.

Claude Code

• London
• Hybrid
• £140,000 – £180,000 pa
• Mid-level

Draft, review and negotiate complex commercial and procurement contracts, including SaaS, reseller, services and IP licensing agreements, for enterprise customers, vendors and partners. The role sits within a regional commercial and legal team, translating global legal strategy into local execution, building scalable contracting processes and running enablement sessions across Product, Sales, Finance and Procurement.

• London
• Hybrid
• £255,000 – £325,000 pa
• Lead · manages people

Lead a London-based team building connectivity infrastructure for Claude, including the MCP proxy, OAuth and token management, and official SDKs. The role spans hiring, coaching, roadmap setting with San Francisco partners, and operational rigor for systems that external partners depend on.

MCP · Python · TypeScript +4

• London
• Hybrid
• £195,000 – £245,000 pa
• Senior

Conducts empirical research on AI's economic effects, building and extending the Anthropic Economic Index with regionally-specific analysis. Develops novel measurement methodologies using econometrics, machine learning, and structural estimation, and translates findings into policy recommendations while building relationships with academic, government, and industry partners.

Claude

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Blends reinforcement learning research with engineering, building and scaling RL infrastructure, training environments and evaluations for large language models. Work spans agentic tool use, code generation, reasoning and distributed GPU training, with close collaboration across research, alignment and production teams.

PyTorch · TensorFlow · JAX +3

• London
• Hybrid
• £370,000 – £630,000 pa
• Mid-level

Builds and improves the RL training infrastructure researchers rely on, profiling and rearchitecting bottlenecks across the stack and owning run reliability end-to-end. Works closely with researchers and adjacent teams like inference and sandboxing, spanning low-level performance work through to RL algorithms.

JAX · PyTorch

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Join the Pretraining team to develop the next generation of large language models, working at the intersection of research and engineering. You'll lead small research projects, design and analyse experiments on model architecture, algorithms, data processing and optimizers, and scale distributed training infrastructure across thousands of GPUs.

PyTorch · Kubernetes · GPUs

• London
• On-site
• £260,000 – £630,000 pa
• Mid-level

Owns critical parts of a production pretraining pipeline, covering performance optimization, observability, reliability and hardware debugging across the full stack. Splits time roughly 50/50 between research and engineering, designing experiments to cut step time and boost uptime, and responding to on-call launch incidents. Works in-office in London alongside SF and specialist teams.

JAX · TPU · PyTorch +3

• London
• Hybrid
• £375,000 – £640,000 pa
• Mid-level

Designs and runs large-scale reinforcement learning experiments to understand how RL behaves as model size, compute and task horizon scale, then turns validated findings into production training recipes. Builds long-horizon benchmarks and debugs failures that only surface at the research/infrastructure boundary, working closely with adjacent RL teams.

• London
• Hybrid
• £325,000 – £485,000 pa
• Lead

Sets technical direction for agent-driven compute cluster lifecycle management, covering provisioning, updates and decommissioning across major clouds and own datacenters. Partners with security, research and cloud providers on secure-by-default, high-bandwidth clusters, scalability and fault tolerance, while mentoring engineers and shaping incident response and on-call practices.

Kubernetes · Terraform · AWS +7

• London
• Hybrid
• £325,000 – £390,000 pa
• Lead

Builds and operates large-scale CI infrastructure supporting thousands of daily builds across multiple cloud providers, including intelligent test selection, merge queue management, and incident response automation. Works within the Developer Productivity org on Kubernetes-based test infrastructure, flake detection, and developer tooling for a monorepo.

Buildkite · Jenkins · GitHub Actions +2

• London
• Hybrid
• £325,000 – £390,000 pa
• Senior

Lead and scope multi-month infrastructure projects, making architectural decisions for large-scale distributed systems that train and serve AI models. Work spans Kubernetes clusters, data pipelines, observability and developer tooling, partnering with research and product teams while owning reliability, scalability and security.

Kubernetes · AWS · GCP +6