ML Researcher: Decentralised Training & Open Source, Equity

Machine Learning Researcher – Early-Stage AI Infrastructure

AI - ML

240,000 USD - 360,000 USD Base + Equity California, London 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 ‘View email address on click.appcast.io’ 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) #J-18808-Ljbffr Durlston Partners