Artificial Intelligence Jobs

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Senior technical owner for a portfolio of public sector customers, shaping AI strategy from pre-sales discovery through production adoption. Owns the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, designing architectures spanning models, data, integration, identity, security and governance while coordinating deployment, enablement and partner specialists.

ChatGPT Enterprise · OpenAI API · Codex +3

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Senior technical owner for a named portfolio of enterprise customers, acting as the "CTO of your book of business" from pre-sales discovery through production adoption. Owns the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, designing architectures spanning models, data, integration, security and evaluation while coordinating deployment, enablement and partner specialists.

ChatGPT Enterprise · OpenAI API · Codex +1

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

Founding leader for Anthropic's Forward Deployed Engineering practice, hiring and developing a team of engineers who embed with strategic enterprise customers to ship production AI applications. Player-coach role setting technical and operational standards, building repeatable playbooks, and partnering with Sales, Product and Engineering. Requires travel to customer sites 25-50%.

Claude

• Switzerland
• Remote
• Senior

Design, develop and optimise GPU/CPU-accelerated numerical libraries such as DALI and nvImageCodec, with heavy focus on performance tuning, benchmarking and CUDA-based parallel algorithms. The role also involves setting technical roadmaps with partners and providing technical leadership to other library engineers.

CUDA · DALI · nvImageCodec +1

• Switzerland
• Remote
• Senior

Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python skills plus deep knowledge of ML framework internals and CPU/GPU architectures.

JAX · PyTorch · TensorFlow +4

• London
• Hybrid · 2–3 days in office
• Mid-level

Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.

JAX · NVIDIA Warp · OpenFOAM +2

• London
• Hybrid
• Senior
• Permanent

Lead the development of novel safety evaluations quantifying AI risks in high-impact domains such as CBRN and Cyber, executing original technical research from concept to publication. Shape the R&D agenda, contribute to client delivery and red-teaming for frontier labs, and engage externally with the global research community. The role sits in a central R&D team focused on fundamental and applied technical AI safety research.

Language Models · Generative AI

• London
• Hybrid
• Senior

Own high-level research work-streams, setting technical direction and roadmaps while guiding junior team members. Build deep learning and probabilistic models of physical systems, collaborating with ML and simulation engineers to translate physics challenges into mathematical formulations and production code.

PyTorch · CUDA · JAX +4

• London
• Hybrid · 3 days in office
• Senior

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.

JAX · PyTorch · XLA +6

• London
• Hybrid · 3 days in office
• Senior

Lead the hardening and scaling of an inference platform serving fleets of cutting-edge ML models for scientific applications. Set strategy and roadmaps, architect next-generation services to solve scaling limits, and partner with research, product and operations teams to align infrastructure with biotech R&D cycles.

Kubernetes · Google Cloud Platform · NVIDIA GPU +1

• London
• Hybrid
• Senior
• Permanent

Sets technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms for robust driverless operation. Leads integration into the shared driving stack, aligning ML, inference optimisation and software teams, and mentors through architecture reviews. Works with large-scale training and fleet data in a small, high-impact team.

• 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
• Mid-level
• Permanent

Design, build and deploy secure, scalable cloud infrastructure for AI and ML workflows, working in a cross-functional team with data scientists and ML engineers. The role involves infrastructure-as-code, containerised deployments and client-facing requirements gathering, with a focus on Azure, AWS, Terraform, Docker and Kubernetes.

Azure · AWS · Terraform +3

• London
• Hybrid
• Senior
• Permanent

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

PyTorch · CUDA

• London
• On-site
• £150,000 – £200,000 pa
• Mid-level
• Permanent

Develops and fine-tunes robot manipulation policies using behaviour cloning and reinforcement learning, then trains, evaluates and deploys models onto real humanoid hardware. Works within a specialist Manipulation team alongside simulation, teleoperation and controls engineers to improve sim-to-real transfer and training data quality. Distinct for being hands-on with physical robots rather than purely simulation or research.

PyTorch · JAX · OpenVLA +1