Artificial Intelligence Jobs

Wayve · London

Develop next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Work spans diffusion and transformer architectures, latent compression, context pruning and inference-latency optimisation, with closed-loop agent interaction and sim-to-real evaluation. The role combines ML research, multi-modal modelling and production deployment, including mentoring and publishing.

Isomorphic Labs · London

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.

NVIDIA · Switzerland

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.

NVIDIA · United Kingdom

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, ML framework internals, and CPU/GPU architecture expertise.

Adria Solutions · Huddersfield · £35,000 – £45,000 pa

Supports AWS infrastructure, CI/CD pipelines and automation for software and machine learning workloads, including packaging, versioning and deploying ML models. Works alongside software and AI engineers to keep development, testing and production environments consistent, monitoring pipelines and fixing issues. Suited to an early-career engineer with cloud, scripting and Git foundations and an interest in MLOps.

Ncounter · Manchester · £80,000 – £90,000 pa

Hands-on research engineering role investigating the internal behaviour and security of large language models, turning academic ideas into practical experiments in Python. Work spans model internals, data movement, training risk and safe deployment, alongside production-quality ML engineering, testing and code reviews. Requires active SC clearance and around three days per week on secure sites.

Infused Solutions · London · £65,000 – £75,000 pa

Senior AI EngineerLocation: Remote (UK) or Hybrid - London (1 days per week in the office if London-based)Salary: £65,000 - £75,000 + Excellent BenefitsJob Type: PermanentPlease note: Applicants must have the right to work in the UK. Unfortunately, visa sponsorship...

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.

Ocado · London

Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.

Harnham - Data and Analytics Recruitment · London · £100,000 – £140,000 pa

Build and lead multimodal AI applications spanning text, audio and video, including AI-generated avatars and automated content summarisation, within a growing AI team in a mature data function. The role involves translating business needs into scalable, production-deployed AI products and collaborating with a multidisciplinary team, with technical leadership duties at Lead level.

Ocado · Sofia, Bulgaria

Maintains and improves a live customer-facing slot-availability application while writing Terraform/OpenTofu infrastructure as code for cloud environments. Extends backend services, APIs and data pipelines, and modernises the platform by tuning Airflow/Composer and reducing technical debt. Works in a small distributed team with monitoring, alerting and incident response duties.

eFinancialCareers · London

You will partner with portfolio managers, analysts and researchers to understand investment workflows, then design, build and deploy AI-powered applications and data tools for front-office teams. The role sits in a central Data & AI team, integrating large-scale data, machine learning models and modern software engineering practices in a fast-paced hedge fund environment.

Entrust · Paris, France

Owns planning, coordination and execution of testing across a cross-functional identity verification product team, covering web, mobile, backend services and ML-powered products. Builds maintainable automated test frameworks and suites, mentors colleagues, and contributes to org-wide quality and tooling initiatives. Combines automation with exploratory testing in a team of nine embedded test engineers.

Entrust · London

Owns test planning, coordination and execution within a cross-functional identity verification product team, covering web, mobile, backend and ML-powered journeys. Builds maintainable automated test frameworks, combines automation with exploratory testing, and mentors colleagues while improving CI/CD pipelines and release feedback loops.

Tenth Revolution Group · London · £75,000 – £105,000 pa

Builds and deploys production LLM and Generative AI applications for enterprise clients, including RAG solutions, scalable data pipelines and AI-powered services. Works in a collaborative consultancy team of engineers and architects, applying software engineering best practices to take AI from proof of concept into production, with monitoring and optimisation of live systems.