Artificial Intelligence Jobs

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

NVIDIA · Bristol

Internship on NVIDIA's embedded computing team in Bristol, working with Tegra SoC, DGX Spark and the Jetson Embedded Platform. The role involves building Linux kernel and user-space software, improving the Jetson Developer Kit experience, and accelerating deep learning and neural network technologies for autonomous vehicles, robotics and analytics alongside hardware and software engineers.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working with application developers and collaborating with architecture, research, libraries, tools and system software teams.

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.

Back TO Work · Nottingham · £26,500 pa

An apprenticeship supporting a manufacturing firm's IT and security team, monitoring production networks for unusual activity, responding to alerts, managing user accounts and access permissions, and helping maintain security standards across office and factory systems. The role blends cybersecurity with AI, using AI-powered tools for anomaly detection, automation and reporting dashboards, while learning to protect operational technology and connected devices.

Luminance · Cambridge

An 8-week internship embedded in a software engineering team, working alongside and mentored by an engineer from day one. Interns contribute to real engineering work at a fast-paced AI company, with a MacBook Pro and extra computing resources provided. Requires at least three days a week on-site in Cambridge, with up to two days remote.

Anthropic · London

A four-month, full-time research fellowship working on empirical AI projects in either ML systems/performance or reinforcement learning, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers and aim to produce a public output such as a paper submission, with projects spanning CPU simulators, accelerator backends, synthetic data pipelines, and RL environments.

Faculty · London

A one-week unpaid work placement at Faculty's London offices for UK Armed Forces veterans in their final 12 months of service. Participants gain structured exposure to different roles, processes and people across the Defence Business Unit, seeing how a leading AI company applies machine learning to surveillance, reconnaissance, autonomous systems and combat service support.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working directly with application developers and collaborating with architecture, research, libraries, tools and system software teams.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The role also involves publishing optimisation techniques via developer blogs or conferences and influencing next-generation hardware and software design.