Team Manager, Interpretability

Anthropic • • 4w ago

As one of the managers on the Interpretability team in Anthropic’s research organization, you'll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally.

Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that deeply understanding how AI systems work at a mechanistic level is the most robust way to make advanced systems safe. Our Interpretability work touches nearly all parts of our research org and infrastructure, whether that's designing and running scientific experiments, parallelizing big jobs across multiple servers, optimizing complex programs for throughput and efficiency, improving our dev tooling, or collaborating with other research teams to increase the impact and reach of our discoveries.

Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. You will manage careers and performance, facilitate relationships within and across teams, and shepherd the hiring pipeline. While you will not be primarily responsible for setting the research or technical direction, you will work closely with a Technical Research Lead to prioritize and operationalize the agenda.

We currently have three subteams within Interpretability. These teams all require a blend of engineering and research expertise to accomplish their goals, and as they grow, need project management and people management support to operate smoothly. We believe it is too much for one person to sustainably lead in all four of those disciplines for larger teams. Instead, we prefer to partner Technical Leads with Team Managers to better cover all these expertises. While the default is that the Team Manager would be primarily responsible for the people and project management side of the coin, we have seen other splits work successfully.

Note: We are only open to candidates who can be based in San Francisco, Boston, New York, or London.

Recent Work from the Interpretability Team

Some of our team's notable publications include Towards Monosemanticity: Decomposing Language Models With Dictionary Learning, A Mathematical Framework for Transformer Circuits, In-context Learning and Induction Heads, and Toy Models of Superposition. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread, Multimodal Neurons, Activation Atlases, and Building Blocks.

Our research has recently led to the discovery of multilingual features in large language models. We are actively scaling dictionary learning to larger models and exploring novel approaches to understanding and mitigating obstacles to interpretability like superposition.

Responsibilities:

Partner with a Technical Research Lead to prioritize the team's work in alignment with our overall research strategy and goals
Identify improvements to processes (e.g. research reviews, reading groups, code reviews) and implement solutions that help the team operate effectively
Coach and support your direct reports in their professional growth and development
Run the team's recruiting efforts efficiently, ensuring we can grow rapidly through a period of significant expansion
Communicating team updates and results to other teams and leadership

You may be a good fit if you:

Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well
Are an experienced manager (with at least 2 years of experience) and actively enjoy people management
Have experience with our research or are motivated to learn more about it
Enjoy working on an interdisciplinary team (members of our teams have experience across ML, physics, neuroscience, policy, business and product)

Strong candidates may also have experience with:

At least 1 year of technical experience with research and/or engineering
Strong people management experience, including coaching, performance evaluation, mentorship, and career development
Excellent project management skills, including prioritization and cross-functional coordination
Experience recruiting talent for your team including predicting staffing needs, designing interview loops, evaluating and interviewing candidates, and closing offers
Excellent communication and interpersonal skills
Track record of leading high-performing research or engineering teams
Experience working on open-ended, exploratory research agendas aimed at foundational insights
Familiarity with engineering infrastructure inside fast-moving research teams