Biological Safety Research Scientist

Anthropic Anthropic · AI Frontier · United States · Remote · Safeguards (Trust & Safety)

Research Scientist focused on biological safety for AI systems, applying technical skills to design and develop safety systems that detect harmful behaviors and prevent misuse. This role involves designing and executing capability evaluations, collaborating on training data and safety system training, analyzing performance, and stress-testing safeguards. The goal is to ensure biological safety is embedded throughout the model development lifecycle, balancing AI's potential in life sciences with preventing misuse.

What you'd actually do

  1. Design and execute capability evaluations ("evals") to assess the capabilities of new models
  2. Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers
  3. Analyze safety system performance in traffic, identifying gaps and proposing improvements
  4. Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces
  5. Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle

Skills

Required

  • PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, OR equivalent professional experience
  • Extensive experience in scientific computing and data analysis
  • Proficiency in programming (Python preferred)
  • Deep expertise in modern biology, including both "reading" (e.g. high-throughput measurement, functional assays) and "writing" (gene synthesis, genome editing, strain construction, protein engineering) techniques in biology
  • Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks (e.g., Biological Weapons Convention, Australia Group guidelines)
  • Strong analytical and writing skills
  • Ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders

Nice to have

  • Background in AI/ML systems, particularly experience with large language models
  • Experience in developing ML for biological systems
  • Extensive experience in complex projects with multiple stakeholders

What the JD emphasized

  • dual-use research concerns
  • select agent regulations
  • biosecurity frameworks

Other signals

  • design and develop safety systems
  • detect harmful behaviors
  • prevent misuse
  • translate biosecurity concepts into technical safeguards
  • model development lifecycle