Advance the frontier of AI Reinforcement Learning development and delivery
Build the infrastructure and tooling that transforms real-world vulnerability research into large-scale reinforcement learning environments
Create training environments that teach AI systems how to hack and defend software
Work at the intersection of AI, security research, and systems engineering

Strong systems engineer
Understanding of RL training workflows used by modern LLM systems
Experience with DevOps pipelines (e.g., github actions), reproducible builds (docker, buildkit, nix)
Proficiency in Python and C. Other languages (especially Rust) are a plus
Understanding of software vulnerabilities, fuzzing, or program analysis
Experience with build systems and large open-source codebases
Comfort working with Linux systems and low-level debugging
Experience working with benchmark environments (CTFs, SWE-bench, security challenges, etc.) is a plus

Reinforcement Learning Engineer – Cybersecurity

Key skills