Research Manager, Biological Safety

Location: San Francisco, CA, United States; hybrid policy requires staff to work from one of the offices at least 25% of the time

Annual salary: $405,000–$485,000 USD

Company

Anthropic develops reliable, interpretable, and steerable AI systems designed to be safe and beneficial for users and society.

What you will do

• Manage, coach, hire, and develop research scientists and engineers working on biological safety evaluations and classifiers.
• Set the technical direction and roadmap for biological safety research, including prioritization and safeguard release decisions.
• Lead capability evaluations, dataset development, classifier training, and performance measurement against production traffic.
• Direct red-teaming and stress-testing of safeguards as models, threats, and product surfaces evolve.
• Build repeatable tooling and pipelines for evaluation and classifier development.
• Collaborate with Research, Product, Policy, government affairs, and external stakeholders, and represent the work in model cards, policy documents, and other communications.

Requirements

• Experience managing a technical team, including hiring, coaching, and performance management.
• Experience setting technical direction, prioritizing work under uncertainty, and leading complex technical projects.
• Proficiency in Python, scientific programming, data analysis, and quantitative experiment or evaluation design.
• Strong understanding of machine learning fundamentals and modern biology, including high-throughput assays, gene synthesis, genome editing, strain construction, and protein engineering.
• Knowledge of dual-use research and biosecurity frameworks, such as select agent regulations, the Biological Weapons Convention, or Australia Group guidelines.
• Bachelor’s degree or equivalent education, training, or professional experience; visa sponsorship may be available for eligible candidates.

Nice to have

• 3+ years of people management experience, ideally managing research scientists, research engineers, or ML engineers.
• 8+ years of hands-on life sciences experience in molecular biology, drug discovery, computational biology, or a related field.
• Experience with large language models, production classifiers, biological ML systems, adversarial robustness, red-teaming, or ML safety evaluations.
• Experience building a team or function from a small headcount.

Culture & Benefits

• Collaborative research environment focused on a small number of large-scale AI research efforts.
• Frequent research discussions and emphasis on clear technical communication.
• Flexible working hours and an office designed for collaboration.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.