Research Engineer, Cybersecurity RL (Reinforcement Learning)

Anthropic•San Francisco, CA

2d•Hybrid

About The Position

Anthropic is hiring a Research Engineer to help safely advance AI 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, designing and implementing reinforcement learning environments, conducting experiments and evaluations, and delivering work into production training runs. The engineer will collaborate with researchers, engineers, and cybersecurity specialists inside and outside Anthropic. The role requires machine learning experience combined with cybersecurity domain expertise. Participation in an on-call rotation may be required. The Security team protects Anthropic's AI systems and maintains the trust of its users and society. The role also involves partnering with researchers and safety teams to understand analytical needs, building solutions, developing agentic integrations that enable AI systems to investigate and act on analytical findings, and contributing to team strategy and investment decisions. Anthropic describes itself as a collaborative research organization focused on building reliable, interpretable, steerable, safe, and beneficial AI systems. The position follows a location-based hybrid policy: staff are currently expected to spend at least 25% of their time in an office, though some roles may require more. Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration.

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.
At least 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

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