We’re working with a London-based AI startup building the world’s most accessible training infrastructure for large-scale AI models. Inspired by the ‘Folding@Home’ project, their mission is to democratise access to AI by allowing everyday users to contribute compute power via their personal devices.

Since launching in March 2024, they’ve raised ~$20M, open-sourced a project that’s gained 15k GitHub stars in under four months, and built a founding team with strong academic roots, including alumni from Oxford and top international competitions.

They’re now hiring a Machine Learning Researcher to join their team. You’d be joining early enough to influence the future of a high-impact, technical product, but with the backing of top-tier investors and strong early traction.

The Role:

• Conduct applied ML research to help make decentralised model training a practical reality.
• Contribute to both infrastructure and core ML problems, including training dynamics, distributed optimisation, and scaling laws.
• Collaborate closely with software engineers to productionise your ideas and open-source contributions.

Requirements:

• Strong background in ML research, recent postdocs or early-career researchers welcome.
• Experience working on model training (LLMs, diffusion models, or related).
• High levels of curiosity and a bias toward experimentation and building.
• Ideally, competition experience (ICPC, IOI, IMO, IPhO)