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Reinforcement Learning Infrastructure (Cybersecurity)

1 hour, 16 minutes ago
United States
Full-time
Lead
Machine Learning Engineer
Artificial Intelligence and Machine Learning
C Docker GitHub Actions Linux Python Reinforcement Learning Rust
Apply Now
Bugcrowd

Bugcrowd

Bugcrowd provides a crowdsourced cybersecurity platform that connects organizations with elite security researchers to enhance security measures through managed bug bounty programs, penetration testing, and vulnerability disclosure initiatives.

Internet Software & Services
1K-5K
Founded 2012
$79M raised
View All Jobs 19

Description

  • Design pipelines that ingest software projects and automatically construct reinforcement learning training environments.
  • Build infrastructure and tooling for authentic cybersecurity RL environments used by foundation model companies.
  • Work at the intersection of AI, security research, and systems engineering to support vulnerability discovery, exploitation, and remediation training.
  • Integrate Bugcrowd’s Mayhem platform into environment-generation workflows.
  • Develop high-performance, reproducible Linux-based machine learning environments and related tooling.
  • Support the delivery of training environments used by frontier AI labs.
  • Contribute to systems that generate large volumes of environments rather than a single application.
  • Collaborate on infrastructure that advances autonomous cybersecurity research and AI model training.

Requirements

  • Experience with reinforcement learning workflows used by modern LLM systems.
  • Strong proficiency in Python and C; Rust is a plus.
  • Experience with DevOps pipelines such as GitHub Actions.
  • Experience with reproducible build and container tools such as Docker, BuildKit, and Nix.
  • Knowledge of software vulnerabilities, fuzzing, or program analysis.
  • Background in binary exploitation, including buffer overflows, exploitation, fuzzing, and x86/64.
  • Comfort working with Linux systems and low-level debugging.
  • Experience with build systems and large open-source codebases.
  • Experience building clean, reproducible Linux ML environments, including containers and MCP.
  • Experience with benchmark environments such as CTFs, SWE-bench, or security challenges is a plus.

Benefits

  • Base salary range of $176,400 to $242,550.
  • Eligibility for a discretionary bonus program or commission plan.
  • 100% remote, work-from-home arrangement.
  • Flexible compensation approach tailored to business needs.
  • Reasonable accommodations for applicants and employees with disabilities.
  • Commitment to inclusion and equal employment opportunity.

Interested in this position?

Apply directly on the company website

Apply Now

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