Researcher, Alignment Interpretability
OpenAI · San Francisco
About this role
**Researcher, Alignment Interpretability** **About the Team** The Interpretability team studies internal representations of deep learning models, focusing on understanding model behavior and engineering models with more understandable representations. The team applies this understanding to ensure alignment of powerful AI systems through a collaborative, curiosity-driven approach. **About the Role** OpenAI seeks a researcher passionate about understanding deep networks to develop and execute research plans in mechanistic interpretability. You'll work closely with a highly motivated team to help ensure future models remain safe as capabilities grow. **Key Responsibilities** • Develop and publish research on techniques for understanding deep network representations • Engineer infrastructure for studying model internals at scale • Collaborate across teams on projects OpenAI is uniquely positioned to pursue • Guide research directions toward demonstrable usefulness and long-term scalability **Ideal Candidate** • Excited about OpenAI's mission to ensure AGI benefits all of humanity • Passionate about long-term AI safety & alignment with deep technical thinking • Experience in AI safety, mechanistic interpretability, or related disciplines • Ph.D. or research experience in computer science, machine learning, or related field • 2+ years of research engineering experience with Python or similar languages • Thrives with large-scale AI systems and deeply curious mindset **About OpenAI** An AI research and deployment company dedicated to ensuring general-purpose AI benefits all of humanity. OpenAI is an equal opportunity employer committed to diversity and inclusion.
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