Research Engineer / Performance Engineer, RL Distributed Systems

Highlights

• Build distributed systems that run frontier RL for Claude at scale.
• Keep training, sampling and environments progressing through failures.
• Remove system limits across scheduling, data movement and observability.

What they offer

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours

Ideal candidate

A systems generalist who has operated large distributed systems and loves reasoning from first principles. You chase the most important bottleneck, sweat correctness under failure, and want to shape frontier RL.

Requirements

• Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go
• Experience designing, building, and operating large-scale distributed systems in production
• Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery
• Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network
• Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally
• Strong written communication, including design documents and incident writeups
• Experience running ML training or inference infrastructure at scale
• Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration