Reinforcement Learning Engineer (Cybersecurity)

Responsibilities

• ▹Design pipelines that ingest software projects, analyze them with Bugcrowd's Mayhem platform, and automatically construct training environments
• ▹Build reinforcement learning workflows
• ▹Build clean, reproducible Linux ML environments (containers, MCP, etc.)
• ▹Apply system security expertise in binary exploitation (buffer overflows, fuzzing, x86/64)
• ▹Develop applications in Python and C

Requirements

• ▹Understanding of RL training workflows used by modern LLM systems
• ▹Experience with DevOps pipelines (e.g. GitHub Actions) and reproducible builds (Docker, buildkit, Nix)
• ▹Proficiency in Python and C
• ▹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

Nice to have

• ▹Rust experience
• ▹Experience with benchmark environments (CTFs, SWE-bench, security challenges)

Soft skills

What we offer

• ▹Base pay range: $176,400–$242,550 (US national average)
• ▹Eligible for discretionary bonus or commission plan
• ▹100% remote, work-from-home

About the company

Bugcrowd has run a crowdsourced cybersecurity platform since 2012, connecting a global network of ethical hackers with its AI-powered Security Knowledge Platform (CrowdMatch™). Headquartered in San Francisco and New Hampshire, it is backed by General Catalyst, Rally Ventures, and Costanoa Ventures.