[Expression of Interest] Research Manager, Interpretability

Anthropic
SF office2025-11-07

About the job

As a manager on the Interpretability team, 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. 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. In this role, you will partner closely with an individual contributor research lead to drive the team's success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline.

Responsibilities

Partner with a research lead on direction, project planning and execution, hiring, and people development

Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively

Coach and support team members to have more impact and develop in their careers

Drive the team's recruiting efforts, including hiring planning, process improvements, and sourcing and closing

Help identify and support opportunities for collaboration with other teams across Anthropic

Communicate team updates and results to other teams and leadership

Maintain a deep understanding of the team's technical work and its implications for AI safety

Qualifications

Minimum

Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams

Have a background in machine learning, AI, or a related technical field

Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles

Have strong project management skills, including prioritization and cross-functional coordination and collaboration

Have managed technical teams through periods of ambiguity and change

Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research

Are a strong communicator both in speaking and in writing

Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well

Preferred

Experience scaling engineering infrastructure

Experience working on open-ended, exploratory research agendas aimed at foundational insights

Some familiarity with our work and mechanistic interpretability