[Expression of Interest] Research Manager, Interpretability
Anthropic · San Francisco, CA · AI Research & Engineering
About this role
Anthropic is hiring a manager-level Research Scientist in the machine learning function based in San Francisco, CA. The posting calls out experience with HTML/CSS, LLMs, Deep Learning, Git. Compensation is listed at $350,000–$500,000 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- manager
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- AI Research & Engineering
More roles at Anthropic
Job description
from Anthropic careersAbout Anthropic
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.
Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists. If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply.
About the Interpretability team:
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, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe.
People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer".