[Hiring] Reinforcement Learning Engineer @Bugcrowd

Role Description

The Bugcrowd RL and Reasoning Team focuses on pushing the boundaries of autonomous cybersecurity by building authentic, verifiable reinforcement learning environments for world-leading foundational AI companies. As a Reinforcement Learning Engineer specializing in Reinforcement Learning from Verifiable Rewards (RLVR), you will:

• Design and scale automated verification pipelines that transform real-world software vulnerabilities into deterministic reward functions.
• Bridge the gap between low-level security analysis and modern LLM reasoning models.
• Engineer environments where AI agents learn to discover, exploit, and remediate software vulnerabilities with mathematical certainty.
• Power rigorous, verifiable reward signals that teach next-generation frontier AI models how to master complex cybersecurity domain logic.
• Work at the intersection of fuzzing, dynamic program analysis, system exploitation, and scalable ML infrastructure.

Qualifications

• Understanding of RL training workflows used by modern LLM systems, specifically execution-based feedback or Reinforcement Learning from Verifiable Rewards (RLVR).
• Proficiency developing applications in Python and low-level systems programming in C, with Rust experience being a strong plus.
• Solid understanding of software vulnerabilities, binary exploitation, fuzzing methodologies, or program analysis.
• Experience with DevOps pipelines (e.g., GitHub Actions), reproducible builds (Docker, BuildKit, Nix), and comfort working with Linux systems and low-level debugging.
• Experience working with or building benchmark environments (e.g., CTFs, SWE-bench, security challenges, or execution sandboxes).

Requirements

• Design, build, and deploy high-throughput RLVR environments that evaluate LLM action sequences against deterministic execution outcomes.
• Develop automated test harnesses, sandboxes, and verification engines that convert complex vulnerability research into binary pass/fail reward signals.
• Integrate Bugcrowd’s Mayhem automated analysis platform and real-world vulnerability feeds into continuous, scalable RL environment generation pipelines.
• Architect safe, isolated, and highly reproducible execution environments capable of running thousands of simultaneous agent-driven exploitation and patching trajectories.
• Collaborate directly with researchers at frontier AI labs to define standard benchmark formats, observation spaces, and verifiable evaluation metrics for cybersecurity tasks.
• Implement precise telemetry, ground-truth verification algorithms, and trajectory logging to analyze agent reasoning paths and prevent reward hacking or false positives.
• Build low-level instrumentation and debugging tools to monitor memory states, process executions, and network behaviors during agent interaction cycles.
• Optimize infrastructure performance and environment reset latency to support massive-scale parallel sampling and distributed RL training workflows.
• Benchmark and evaluate frontier AI model performance across diverse offensive and defensive security challenges.

Benefits

• Competitive salary range of $176,400 - $242,550.
• Eligibility to participate in a discretionary bonus program or commission plan.

Company Description

At Bugcrowd, we understand that diversity in the workplace is vital to a company’s success and growth. We strive to make sure that people are included and have a sense of being part of making Bugcrowd not only a great product but a great place to work.

• Our team consists of a broad range of people: musicians, adventure sports junkies, nature lovers, parents, cereal enthusiasts, night owls, cyclists, artists.
• We value the perspectives and experiences people from underrepresented backgrounds bring.