Research Engineer, Machine Learning (RL Velocity)

Details

Anthropic’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 Anthropic, 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.

The annual compensation range for this role is listed below.

Annual Salary: £370,000 - £630,000 GBP

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 Anthropic does RL at scale

Requirements / Qualifications

• Strong software engineering fundamentals and a track record of building performant, reliable systems
• Experience working on ML infrastructure, distributed systems, or research tooling
• Comfortable operating across the stack, from low-level performance work to RL algorithms
• Bias toward shipping and iterating quickly, with a mix of high agency and low ego
• Minimum education: Bachelor’s degree or 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: will correlate with internal job level requirements for the position

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

Logistics

• Location: London, UK
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• Visa sponsorship: We do sponsor visas. If an offer is made, the company will make every reasonable effort to obtain a visa and retains an immigration lawyer to help.
• Deadline to apply: None. Applications are reviewed on a rolling basis.

How we're different

Anthropic works as a single cohesive team on a few large-scale research efforts. The company values impact on steerable, trustworthy AI, collaboration, and strong communication skills. Recent research directions include GPT-3, interpretability, scaling laws, AI & compute, and learning from human preferences.

Come work with us

Anthropic is a public benefit corporation headquartered in San Francisco. They offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office spaces for collaboration. Guidance on candidates' AI usage is provided in their candidate AI guidance policy.