Anthropic is seeking an Interpretability Researcher to understand how neural networks represent and process information. You will develop new techniques for mechanistic interpretability, analyze model internals, and contribute to making AI systems more transparent and trustworthy.
Requirements
- PhD in ML, neuroscience, physics, or mathematics
- Research experience in interpretability or related fields
- Strong mathematical foundations
- Proficiency in Python and PyTorch/JAX
- Ability to communicate complex ideas clearly
Nice to Have
- Published work in mechanistic interpretability
- Experience with sparse autoencoders or probing methods
- Background in neuroscience or cognitive science
- Experience with visualization tools for neural networks
Benefits
- Generous research budget
- Conference and education stipend
- Sabbatical program
Skills
Interpretability Mechanistic Interpretability PyTorch Research Mathematics Python
#J-18808-LjbffrInterpretability Researcher in san francisco at Unknown Company
This position is listed as full time and onsite.