Reinforcement Learning Environments Engineer - Cybersecurity
Preference Modelabout 5 hours ago
San Francisco, CA, USAMid Level / Senior
Responsibilities
- Design and build RL environments and reward functions for security tasks.
- Create environments covering the full vulnerability lifecycle: discovery, exploitation, and patching.
- Develop environments for reverse engineering tasks across various code types.
- Construct verifiable reward signals using various security tools.
- Collaborate with team members to brainstorm and improve environment building.
Requirements
- Strong security fundamentals with interests in offensive and defensive work.
- Hands-on experience in finding, exploiting, or patching vulnerabilities.
- Proficiency in Python and systems programming, with comfort in low-level languages.
- Familiarity with security tooling such as fuzzers and debuggers.
- Problem-solving skills with a drive for end-to-end solutions.
Benefits
- Competitive cash and equity compensation.
- Ownership and autonomy in a fast-moving startup environment.
- Opportunity to work with top machine learning engineers.
- Health, vision, dental benefits.
- 401K match and visa sponsorship available.