Research Manager, Biological Safety

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.

Anthropic's Safeguards organization builds the policies, evaluations, and enforcement systems that keep our models from contributing to catastrophic harm. We are hiring a manager to lead the research engineering team responsible for biological safety: the evaluations, datasets, and classifiers that govern how our models handle biological knowledge.

You will lead a team of research scientists and engineers who design and run capability evaluations against frontier models, curate training data for our safety classifiers, train and iterate on those classifiers alongside our ML engineers, and measure how they hold up against adversarial pressure in production traffic. You will set the technical direction for that work, decide where the team invests, and own the results.

This is a hands-on management role. Most of your time goes to growing and directing the team, but you will keep enough technical depth to review an eval design, interrogate a classifier's failure modes, and represent the work credibly to Research, Product, and Policy partners.

The core tension your team owns is precision: safeguards need to be robust against sophisticated actors while staying out of the way of the far larger population of legitimate researchers using Claude to accelerate life sciences work. Getting that tradeoff right is an empirical problem, and your team is the one measuring it.

• Manage, coach, and grow a team of research scientists and engineers working on biological safety evaluations and classifiers, including hiring, onboarding, performance, and career development

• Set the technical direction and roadmap for the biological safety research agenda, and make the calls about what the team builds, what it deprioritizes, and when a safeguard is ready to ship

• Own the quality of capability evaluations that assess what new models can do in the biological domain, and turn results into deployment recommendations that leadership can act on

• Guide the development of training and evaluation datasets for our safety classifiers, working with internal and external threat modeling experts to ground them in realistic risk

• Oversee the training and iteration of safety classifiers alongside ML engineers, optimizing jointly for adversarial robustness and low false-positive rates

• Ensure the team invests in the tooling and pipelines that make evaluation and classifier development fast and repeatable

• Establish how the team measures classifier and eval performance against production traffic, identifies gaps, and prioritizes improvements

• Direct red-teaming and stress-testing of safeguards as threats, models, and product surfaces evolve

• Partner with Research, Product, Policy, and government affairs colleagues to embed biological safety throughout the model development lifecycle, and serve as an escalation point for biological content

• Represent the team's work in external communications including model cards, blog posts, and policy documents

• Track developments in biology, machine learning, and biosecurity for their potential to create new risks or enable new mitigations

• Experience managing a technical team, including hiring, coaching, and performance management

• A record of