# Research Engineer / Performance Engineer, RL Distributed Systems at Anthropic

- Company: Anthropic
- What the company does: Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. Backed by Accel, Bessemer and General Catalyst.
- Company website: https://www.anthropic.com/
- Type: Startups (AI role)
- Level: Mid level
- Location: San Francisco, CA | New York City, NY | Seattle, WA
- Work setup: On-site
- Posted: 2026-09-29
- Apply by: 2026-11-13
- Apply: https://job-boards.greenhouse.io/anthropic/jobs/5438030008?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/anthropic-research-engineer-performance-engineer-rl-distributed-systems/

## About the role

Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- 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

Tags: AI Research & Engineering

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/anthropic-research-engineer-performance-engineer-rl-distributed-systems/