At a Glance
- Tasks: Build and enhance the RL training infrastructure for cutting-edge research.
- Company: Join Anthropic, a leader in AI research with a focus on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and rapid iteration.
- Why this job: Make a real impact by improving machine learning systems that drive research forward.
- Qualifications: Strong software engineering skills and experience in ML infrastructure or distributed 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.
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
Research Engineer, Machine Learning (RL Velocity) in London employer: Menlo Ventures
Legora is an exceptional employer that champions innovation and collaboration in the legal tech space. With a commitment to diversity and inclusion, employees thrive in a high-performance culture that encourages personal and professional growth. The company offers unique opportunities to work alongside leading global firms, empowering you to make a meaningful impact while shaping the future of legal operations.
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