Research Engineer, Machine Learning (RL Velocity)
$500k - $850k • Remote • Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NY
Posted 1mo ago
Job Location
Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NY
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
The RL Velocity team is responsible for the efficiency and reliability of Anthropic's RL Science stack, which includes the infrastructure, tooling, and systems that enable researchers to iterate quickly on training runs. As a Research Engineer on this team, you will build and enhance the core platform that supports RL development at Anthropic. Your work will focus on removing bottlenecks that slow down research and making it easier for the broader organization to ship better models faster, leading to high-leverage improvements that compound across researchers and runs.
Responsibilities
- Build and improve RL training infrastructure for researchers.
- Identify and resolve bottlenecks in the RL stack through debugging, profiling, and rearchitecting.
- Collaborate with researchers and adjacent engineering teams to understand pain points and deliver faster tooling.
- Ensure the reliability and performance of research runs.
- Contribute to design decisions for scaling RL at Anthropic.
Requirements
- Strong software engineering fundamentals and experience building performant, reliable systems.
- Experience with ML infrastructure, distributed systems, or research tooling.
- Ability to enable others' work through platforms.
- Comfort operating across the full stack, from low-level performance to RL algorithms.
- Bias towards shipping and iterating quickly with high agency and low ego.
- Experience with large-scale distributed training (RL, pre-training, or post-training).
- Familiarity with JAX, PyTorch, or similar ML frameworks.
- Track record of operating at the intersection of research and infrastructure in a fast-moving environment.
- Bachelor's degree or equivalent combination of education, training, and experience in a relevant field.
Benefits
- Competitive compensation
- Generous vacation and parental leave
- Flexible working hours
- Optional equity donation matching
- Visa sponsorship