RL Infrastructure Engineer: Accelerate Research Velocity

Anthropic; York and North Yorkshire; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Health Insurance

Fertility Benefits

Parental Leave

Flexible PTO

Mental Health

Salary & Equity

Equity Matching

Retirement Plans

Life & Income Protection

Wellness Stipend

Commuter Benefits

Education Stipend

Home Office Stipend

Relocation Support

Meal Service

Job summary

Anthropic’s RL Velocity team is seeking a Research Engineer to build and improve the RL training infrastructure researchers rely on daily, removing bottlenecks and enabling rapid iteration across experiments.

You will own the reliability and performance of research runs end-to-end, collaborating with researchers and adjacent engineering teams to ship scalable tooling that accelerates progress in RL at scale.

Qualifications

• 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.
• Bias toward shipping and iterating quickly, with a mix of high agency and low ego.
• Comfortable across the stack, from low-level performance work to RL algorithms.
• Strong software engineering fundamentals and a track record of building performant, reliable systems.
• Experience with large-scale distributed training (RL, pre-training, or post-training).
• Familiarity with JAX, PyTorch, or similar ML frameworks.

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 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.

Skills

Python

Distributed systems

Performance optimization

Software engineering fundamentals

RL algorithms

Education

Bachelor’s degree or equivalent

Tools

PyTorch

JAX

TensorFlow

Job description

Anthropic’s RL Velocity team is seeking a Research Engineer to build and improve the RL training infrastructure researchers rely on daily, removing bottlenecks and enabling rapid iteration across experiments.

You will own the reliability and performance of research runs end-to-end, collaborating with researchers and adjacent engineering teams to ship scalable tooling that accelerates progress in RL at scale.