Security Engineer / Research Engineer, RL Security

Job summary

Responsibilities

Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts.

• Design, build, and operate security controls for RL training systems and the infrastructure they run on
• Work across the stack (orchestration, environments, training, inference) wherever the work is needed
• Review designs and code across the RL stack, find security problems, and fix them
• Build shared libraries and tooling that other RL engineers and researchers build on
• Build the observability needed to understand what these systems are doing

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 or security systems in production
• Strong understanding of security fundamentals
• Working knowledge of Linux, containers, and cloud infrastructure
• Experience debugging complex problems across many hosts and services

Tech stack

• Python
• Rust
• C++
• Kubernetes