Reinforcement Learning Engineer
Skills
DevopsBuffer Social Media ManagementManagementEasily AdaptableEnhanced Data Rates For GSM EvolutionFairness OpinionsFederal Law
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Understanding of RL training workflows used by modern LLM systems
- Experience with DevOps pipelines and reproducible builds
- 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
- Experience with benchmark environments such as CTFs or SWE-bench
Nice to have
- Rust experience
- Security background
- Systems mindset
- Benchmark experience
- Low-level debugging
Day to day
- Design and build large-scale reinforcement learning environments that turn real-world vulnerability research into training data for frontier AI systems
- Develop robust pipelines that ingest software projects analyze them with security tooling and automatically construct reproducible Linux-based environments
- Work at the intersection of AI security research and systems engineering to enable models to learn vulnerability discovery exploitation and remediation
Hiring process
- Apply at Bugcrowd careers page