Distributed RL Systems Engineer — Scale & Reliability

Anthropic Limited; San Francisco (CA); Hybrid; USD 500,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer for the Distributed Systems team within RL Engineering to work on the current system limits across scheduling, data movement, storage, networking, and coordination. This role focuses on building scalable, fault-tolerant, and observable infrastructure for large-scale RL workloads.

As a generalist engineer, you will move across layers, reason from first principles, and choose impactful problems with minimal prior constraints.

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.

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

Skills

Python

Rust

C++

Go

Distributed systems

Performance

Design docs

Education

Bachelor's degree

Tools

Kubernetes

Docker

Job description

Anthropic is seeking a Research Engineer for the Distributed Systems team within RL Engineering to work on the current system limits across scheduling, data movement, storage, networking, and coordination. This role focuses on building scalable, fault-tolerant, and observable infrastructure for large-scale RL workloads.

As a generalist engineer, you will move across layers, reason from first principles, and choose impactful problems with minimal prior constraints.