Research Engineer, Cybersecurity RL (Reinforcement Learning)

Location: San Francisco, CA or New York City, NY; hybrid policy requires staff to work from one of the offices at least 25% of the time, with some roles requiring more office time.

Annual salary: $1–$2 USD.

Company

Anthropic develops reliable, interpretable, and steerable AI systems, with a Security team focused on protecting its AI systems and maintaining user and societal trust.

What you will do

• Partner with researchers and safety teams to understand analytical needs and build solutions.
• Design and implement reinforcement learning environments, conduct experiments and evaluations, and deliver work into production training runs.
• Develop agentic integrations that enable AI systems to autonomously investigate and act on analytical findings.
• Advance defensive cybersecurity capabilities in incident response, security analysis, and vulnerability remediation.
• Contribute to strategic decisions about what to build, partnerships, and investment priorities.
• Collaborate with researchers, engineers, and cybersecurity specialists; participate in an on-call rotation when required.

Requirements

• Experience with machine learning.
• Experience in cybersecurity research.
• Strong software engineering skills.
• Ability to balance research exploration with engineering implementation.
• Bachelor’s degree or an equivalent combination of education, training, and experience.
• A field relevant to the role, demonstrated through coursework, training, or professional experience.
• Experience requirements correlate with the internal job level for the position.
• Commitment to developing safe and beneficial AI systems.

Nice to 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 another experimental and research background.
• Familiarity with reinforcement learning techniques and environments.
• Familiarity with LLM training methodologies.

Culture & Benefits

• Collaborative research environment focused on a small number of large-scale efforts and long-term AI safety goals.
• Frequent research discussions and strong emphasis on communication.
• Flexible working hours and office-based collaboration.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Visa sponsorship may be available; sponsorship cannot be guaranteed for every role or candidate, but Anthropic provides reasonable efforts and immigration-lawyer support.

Hiring process

• Review Anthropic’s guidance on candidate use of AI during the application process.
• Apply even if every listed qualification is not met.