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.

Copello · Bristol · £54,000 – £58,000 pa

Develops and evaluates image processing, computer vision and deep learning algorithms for imaging sensor systems, covering segmentation, noise removal, tracking, pose estimation and classification. Works on-site in Bristol within a cross-functional team, supporting research into emerging AI/ML technologies and integrating algorithms into larger operational systems.

Flarebright · Bicester · £39,000 – £49,000 pa

Contributes across the full development lifecycle, from concept and algorithm design to system integration, testing and troubleshooting of safety-critical navigation and autonomy software in C++. Works with a multidisciplinary team on real-time embedded systems, hardware/software-in-the-loop testing and flight test activities, producing design documentation and test reports.

Anthropic · London · £260,000 – £630,000 pa

Join the Pretraining team to develop next-generation large language models, working across model architecture, algorithms, data processing and optimizer development. You'll lead small research projects, design and analyse experiments, and scale distributed training infrastructure to thousands of GPUs, balancing research goals with practical engineering.

Amazon · Cambridge

Joins a research team advancing multimodal deep learning for consumer devices, focusing on dataset curation, annotation pipelines and automated evaluation methods such as fine-tuned LLM-as-judge. Analyses large offline and online datasets in Python to diagnose model failures and works with training, compiler and product teams to move models from prototype to production.