Research Engineer, Cybersecurity RL (Reinforcement Learning) en Anthropic

Híbrido - Zürich, CH

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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.

Requirements

Skills

  • Machine learning experience
  • Cybersecurity research experience
  • 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
  • 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 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
  • May require participation in an on-call rotation

Technologies

Reinforcement learningLLM training methodologies

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