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.
When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?"
The Interpretability team’s mission is to reverse engineer how trained models work. We believe that a mechanistic understanding is the most robust way to make advanced systems safe.
A few places to learn more about our work and team are this introduction to Interpretability from our research lead, Chris Olah; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results.
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. Your primary responsibilities will be people, project and performance management.
Recent Work from the Interpretability Team
Some of our team's notable publications include Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet, 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.
- 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
- 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 recent experience) with a track record of leading high-performing research or engineering teams and actively enjoy people management
- Have at least 5 years of technical experience with research and/or engineering
- 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 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
- Experience working on open-ended, exploratory research agendas aimed at foundational insights
- Familiarity with engineering infrastructure inside fast-moving research teams
- This role is expected to be in our SF office for 3 days a week.
The expected salary range for this position is:
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're differentWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.