Machine Learning Jobs

CureAge Therapeutics · London

Lead the computationally guided design of a lipid nanoparticle delivery platform, applying chemical and biophysical principles to optimise LNP composition and formulation. Use AI-enabled chemistry, cheminformatics, predictive models and molecular modelling to prioritise formulation components, working closely with the experimental team and founding team in a small start-up.

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.

Cambridge Consultants · United Kingdom

A paid 6-12 month PhD internship in the AI & Algorithms department, working across the full robotic learning pipeline from data collection and model training to deployment on real hardware. Interns join mixed-discipline teams on client projects in healthcare and industrial settings, contributing to internal R&D and using labs, robotic platforms and compute resources.

Cambridge Consultants · United Kingdom

Six- to twelve-month AI and algorithms internship for PhD or Master's students, working alongside engineers on client projects involving modelling, training, testing and data wrangling. Interns also contribute to internal R&D, building on state-of-the-art AI literature, and present results to colleagues and clients. Requires strong Python, Git and demonstrable research experience, plus UK security clearance eligibility.

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 CPU and GPU architectures. The role also involves publishing optimisation techniques via developer blogs or conferences and influencing next-generation hardware, software and programming models.

NVIDIA · Zürich, Switzerland

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 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.

Amazon · London

PhD students join an Amazon Science team to own an end-to-end research project, from scoping with a mentor to deploying algorithms, models or systems into production. Projects span computer vision for Prime Video quality, multimodal AI for Rufus, automated reasoning and formal verification, observability for distributed systems, and recommendation models. Interns may publish at top-tier conferences or see their work ship before the internship ends.

Cambridge Consultants · United Kingdom

Work on multidisciplinary engineering projects across consumer, industrial, and defence sectors, designing embedded systems, writing firmware in C or SystemVerilog, and developing hardware for innovative products. Engage in full project lifecycles from requirements to handover, with mentorship to grow technical and systems design expertise. Projects include robotics, AI-driven security solutions, and collaborative product development with major clients.

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.

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 performance 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.