The opportunity
When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?
What you'll do
Our Research blog: covering advances including Monosemantic Features and Circuits
An Intro to Interpretability from our research lead, Chris Olah
The Urgency of Interpretability from CEO Dario Amodei
Engineering Challenges Scaling Interpretability: directly relevant to this role
Minutes segment: see a demo of tooling our team built
New Yorker article: what it's like to work on one of AI's hardest open problems
What they're looking for
- Security : design the secure-by-default environments and access patterns that: enable deep model access for an organization whose research requires it - done well, the same design improves both our security posture and research productivity.
- Privacy : build data-access patterns that ensure policy adherence as our: research moves from theory into practical application
- Data & Compute Management: manage research data at petabyte scale and make efficient use of large accelerator fleets - storage lifecycle, capacity planning, and scheduling.
- Developer experience: agentic engineering, tooling and observability that keep researchers moving fast
