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Research Engineer / Performance Engineer, RL Distributed Systems

Anthropic· AI Research & Engineering
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Hybrid (San Francisco, CA), Hybrid (New York City, NY), Hybrid (Seattle, WA)$500k - $850kFull-timePosted 3w ago

About the role

Research Engineer on the Distributed Systems team within RL Engineering who designs, builds, and operates large-scale RL infrastructure and tooling to support training, sampling, and environment execution at frontier scale.

Responsibilities

  • Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution
  • Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination
  • Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention
  • Design resource management and autoscaling so that compute follows demand as a run's needs shift
  • Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results
  • Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely
  • Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism
  • Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build

Qualifications

  • 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

Skills

Required:PythonSystems programming (Rust/C++/Go)Distributed systems design
Nice to have:Observability and incident response

Benefits

  • Competitive compensation
  • Generous vacation and parental leave
  • Flexible working hours
  • Office space in San Francisco
  • Optional equity donation matching
Last updated Sep 30, 2026. Interested? Apply on the company site.

About Anthropic

building reliable, interpretable, and steerable AI systems

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

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