Artificial Intelligence Jobs

Wayve · London

Owns the technical vision and architecture for a platform that lets model engineers deploy, run, evaluate and improve ML models over petabytes of driving data and large GPU fleets. Combines hands-on backend engineering in Python with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.

Wayve · London

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.

Multiverse · London

Owns the end-to-end journey for a portfolio of Enterprise accounts, from sales handover through launch, adoption and renewal. Builds 12-month mutual action plans, runs executive business reviews and correlates learner data with client KPIs to prove ROI and drive expansion. Acts as the internal voice of the customer, aligning delivery, product and support teams.

Multiverse · London

Bridges People strategy with hands-on technical product management, building an AI-native People function from the ground up. Owns the vision, strategy and quarterly roadmap for internal People Ops technology, covering core HR systems, integrations, data flows, identity and automation for ~1000 employees. Requires systems thinking and influence across People, Engineering, Security, Compliance, Legal and Analytics.

Scale AI · London

Interns own real, shipped work on the same roadmaps as full-time engineers, building agentic AI applications, evaluation infrastructure, data pipelines and fraud-detection systems for Scale's Global Public Sector team. Work spans Python, TypeScript, React and MongoDB, with mentorship and a strong ownership culture.

University of Bristol · Bristol · £44,746 – £50,253 pa

Builds and operates the software-defined compute and storage/networking platforms behind the UK's most powerful supercomputer, using Python, Rust, Terraform/OpenTofu, Kubernetes, Git and Bash. Works closely with AI researchers to co-design and debug massive-scale GPU and CPU/GPU workloads, with a focus on stability, security and scaling.

ECM Selection · Cambridge · £40,000 – £70,000 pa

This role involves developing end-to-end machine learning systems integrated with advanced electronics for defence and security applications. You'll work across diverse domains such as computer vision and generative models, building functional prototypes and demonstrators. The role emphasizes innovation, rapid iteration across projects, and close collaboration in a technically driven, low-management environment.

University of Surrey · Guildford · £21,805 pa

Develops a computational framework combining computer vision, graphics and machine learning to speed up and improve cinematic camera lens design and simulation. The work covers forward simulation of candidate lens configurations and inverse design of lens architectures against imaging or perceptual objectives, using differentiable rendering and data-driven models. Based at the Vision, Speech and Signal Processing group under Dr Marco Volino and Dr Jean-Yves Guillemaut, with close industry collaboration.

Maritime & Coastguard Agency · Southampton · £45,900 pa

Lead the Maritime Innovation Hub's work on digitalisation, AI, data, connected technologies and autonomous surface ships. You will horizon-scan, build industry and academic networks, produce guidance, and support policy and regulatory colleagues while helping innovators navigate the maritime regulatory regime. The role is outward-facing and international, feeding into the IMO Digitalisation Strategy.

Scale AI · London

Sets standards for responsible AI, model governance and production MLOps across a public sector team, and builds or validates the highest-risk parts of strategic AI systems. Acts as senior technical partner to client leadership, leads severe incident resolution, and coaches other applied AI engineers. Requires deep production AI/ML ownership and experience with regulated, sovereign or on-premise deployments.

Aioi Nissay Dowa Europe · United Kingdom · £81,322 – £112,488 pa

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across multiple client projects. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support pre-sales and use case discovery alongside commercial teams.

Luminance · Cambridge

Builds AI prototypes combining multiple components to solve complex, nuanced tasks, integrating novel agentic technologies such as memory usage and personalization. Productionises solutions into reusable libraries and frameworks, shipping features and tools for large enterprise customers from day one. Works with LLMs like GPT, Claude and Mistral in a fast-moving, quality-focused team.

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

OpenAI · London

Builds and optimizes the large-scale compute platform behind frontier AI, spanning bare-metal automation, Kubernetes scheduling, high-performance networking, storage, and fleet health. Engineers work across the stack, profiling training workloads, improving NCCL and collective communication, and creating tooling that makes heterogeneous clusters reliable and usable.

Amazon · London

Join the Audible Research team to advance computer-generated speech, developing novel deep learning algorithms and modelling techniques for spoken language generation. You will design, evaluate and deploy data-driven models using large-scale computing resources, while leading and mentoring junior engineers and scientists.