Research Engineer, Cybersecurity RL (Reinforcement Learning)

Anthropic•San Francisco, NY

1d•Hybrid

About The Position

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Security team protects Anthropic’s AI systems and maintains the trust of users and society. As a Research Engineer, you will help safely advance model capabilities in incident response, security analysis, vulnerability remediation, and other areas of defensive cybersecurity. The role combines research and engineering: developing novel approaches and implementing them in code. Work includes designing and implementing reinforcement-learning environments, conducting experiments and evaluations, delivering work into production training runs, and collaborating with researchers, engineers, and cybersecurity specialists inside and outside Anthropic. The position requires machine-learning experience combined with cybersecurity expertise. Anthropic expects staff to work from one of its offices at least 25% of the time, although some roles may require more office time. The role may require participation in an on-call rotation. Anthropic sponsors visas, though sponsorship is not possible for every role and candidate.

Requirements

Experience with machine learning.
Experience in cybersecurity research.
Strong software engineering skills.
Ability to balance research exploration with engineering implementation.
Passion for AI’s potential and commitment to developing safe and beneficial systems.
A bachelor’s degree or an equivalent combination of education, training, and/or experience.
A field of study relevant to the role, demonstrated through coursework, training, or professional experience.

Nice To Haves

Professional experience in security engineering, fuzzing, detection and response, or other applied defensive work.
Experience participating in or building CTF competitions and cyber ranges.
Academic research experience in cybersecurity or another experimental and research background.
Familiarity with reinforcement-learning techniques and environments.
Familiarity with LLM training methodologies.

Responsibilities

Design and implement reinforcement-learning environments.
Conduct experiments and evaluations.
Deliver research and engineering work into production training runs.
Collaborate with researchers, engineers, and cybersecurity specialists across and outside Anthropic.
Partner with researchers and safety teams to understand analytical needs and build solutions.
Develop agentic integrations that enable AI systems to autonomously investigate and act on analytical findings.
Contribute to the team’s strategic direction, including decisions about what to build, where to partner, and where to invest.
Participate in an on-call rotation if required.