Scale-Out RL Systems Engineer

Anthropic; New York (NY); Hybrid; USD 500,000 - 850,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching (optional)

Generous vacation and parental leave

Flexible working hours

Job summary

Anthropic is seeking a Research Engineer to join the Distributed Systems team within RL Engineering. You will work on the core distributed infrastructure that trains, samples, and runs sandboxed environments at scale, solving bottlenecks and building robust, observable systems.

Ideal candidates have strong Python and a systems language background (Rust/C++/Go), experience with large-scale distributed systems, and a track record in designing fault-tolerant, high-throughput software.

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 environmental 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 debugging

System design docs

Education

Bachelor's degree

Tools

Kubernetes

Job description

Anthropic is seeking a Research Engineer to join the Distributed Systems team within RL Engineering. You will work on the core distributed infrastructure that trains, samples, and runs sandboxed environments at scale, solving bottlenecks and building robust, observable systems.

Ideal candidates have strong Python and a systems language background (Rust/C++/Go), experience with large-scale distributed systems, and a track record in designing fault-tolerant, high-throughput software.