Research Engineer, Machine Learning (RL Velocity)

About the company: the company’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role: The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at the company, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run.

Responsibilities:

• Build and improve the RL training infrastructure that researchers depend on day-to-day.
• Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed.
• Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster.
• Own the reliability and performance of research runs end-to-end.
• Contribute to design decisions that shape how the company does RL at scale.

You may be a good fit if you:

• Have strong software engineering fundamentals and a track record of building performant, reliable systems.
• Have worked on ML infrastructure, distributed systems, or research tooling.
• Care about enabling other people's work and find leverage through platforms rather than individual experiments.
• Are comfortable operating across the stack, from low-level performance work to RL algorithms.
• Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego.

Strong candidates may also have:

• Experience with large-scale distributed training (RL, pre-training, or post-training).
• Familiarity with JAX, PyTorch, or similar ML frameworks.
• A track record of operating at the edge of research and infra in a fast-moving environment.

The annual compensation range for this role is £370,000 – £630,000 GBP.

Logistics:

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that the company recruiters only contact you from the company.com email addresses. Be cautious of emails from other domains. Legitimate the company recruiters will never ask for money, fees, or banking information before your first day.

How we're different: We believe that the highest-impact AI research will be big science. At the company we work as a single cohesive team on just a few large-scale research efforts. We value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Come work with us! The company is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.