Research Engineer, Machine Learning (RL Velocity)

Menlo Ventures; Greater London; On-site; GBP 370,000 - 630,000; Full time

Job summary

Anthropic is seeking a Research Engineer for the RL Velocity team in Greater London. You will enhance the RL Science stack by building robust training infrastructure and addressing bottlenecks. The background required includes strong software engineering skills, familiarity with ML infrastructure, and the capability to work on both low-level performance and RL algorithms. The role offers a competitive salary between £370,000 and £630,000 GBP per annum, reflective of your skills and experience.

Qualifications

• Strong software engineering fundamentals with a track record of building performant systems.
• Experience with ML infrastructure, distributed systems, and research tooling.
• Ability to leverage platforms over individual experiments.

Responsibilities

• Build and improve the RL training infrastructure for researchers.
• Identify and remove bottlenecks in the RL stack.
• Partner with researchers and engineering teams to enhance tooling.
• Own reliability and performance of research runs.
• Contribute to design decisions for RL at scale.

Skills

Software engineering fundamentals

Performance and reliability systems

ML infrastructure

Distributed systems

Research tooling

Low-level performance work

RL algorithms

Fast iteration and shipping

Education

Bachelor’s degree or equivalent

Tools

JAX

PyTorch

Job description

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.

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

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

Compensation

Annual Salary: £370,000—£630,000 GBP

Minimum qualifications

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