Research Engineer, Cybersecurity RL (Reinforcement Learning)

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Team

The Security team protects Anthropic's AI systems and maintains the trust of our users and society.

About the Role

At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. As a Research Engineer, you'll help to safely advance the capabilities of our models in incident response, security analysis, vulnerability remediation, and other areas of defensive cybersecurity.

This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic.

This role requires ML experience combined with domain expertise in cybersecurity. You might be an ML researcher with a history of cybersecurity work, or a security professional with a background in ML.

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
• This role may require participation in an on-call rotation.

You may be a good fit if you

• Have experience with machine learning.
• Have experience in cybersecurity research.
• Have strong software engineering skills.
• Can balance research exploration with engineering implementation.
• Are passionate about AI's potential and committed to developing safe and beneficial systems.

Strong candidates may also have

• 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 other experimental & research background.
• Familiarity with RL techniques and environments.
• Familiarity with LLM training methodologies.

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