A well-funded AI startup is building software to let anyone train AI models using the spare compute of their personal devices, an open, distributed alternative to billion-dollar clusters. Think: Folding@Home, but for training LLMs.

Founded by a team of Oxford grads and competitive programming talent, they’ve already raised ~$20M and launched a GitHub repo with 15k stars in four months. Now, they’re looking to scale their engineering team with a new wave of smart, ambitious developers.

This is a rare opportunity to work on distributed systems, low-level performance, and machine learning all in one, with the freedom to build in the open and ship quickly.

The Role:

• Build core infrastructure for decentralised AI training and inference.
• Contribute across the stack, from systems-level code to ML pipelines.
• Work closely with researchers and the founding team on a highly technical product.

Ideal Candidates:

• Exceptional programmers with a track record in competitive programming (ICPC finalists, IOI/IMO/IPhO participants, etc.).
• Graduates or early-career engineers preferred, the team is looking for high potential and hunger to grow.
• Strong generalist skills, fast learners, and a passion for building new infrastructure from scratch.