Researcher, Interpretability
Core
Developing and publishing research on techniques for understanding representations of deep networks to ensure the safety of powerful AI systems.
Role type
Researcher, mechanistic interpretability
Builds
Research publications and infrastructure for studying model internals at scale
Domain
Artificial Intelligence, Deep Learning, AI Safety
Deliverable
production ML models
Required skills
mechanistic interpretability, quantitative reasoning, research process, Python, research engineering
Preferred skills
AI safety, long-term AI safety, large-scale AI systems
Technologies
Python
Responsibilities
Develop and publish research on techniques for understanding representations of deep networks, Engineer infrastructure for studying model internals at scale, Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue, Guide research directions toward demonstrable usefulness and/or long-term scalability
Seniority
Senior, hands-on IC