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OpenAIOpenAISan Francisco, CA

Researcher, Interpretability

Conducts research in mechanistic interpretability to understand deep network representations and enhance AI safety. Requires PhD or equivalent in ML/CS, 2+ years research engineering with Python, and passion for safe AGI.

295k – 445k/yr
Hybrid2+ YOEAI Research

About the role

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.

Requirements

  • Excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and aligned with OpenAI’s charter.
  • Enthusiasm for long-term AI safety, and deep thought about technical paths to safe AGI.
  • Experience in the field of AI safety, mechanistic interpretability, or related disciplines.
  • Ph.D. or research experience in computer science, machine learning, or a related field.
  • Thrive in environments involving large-scale AI systems, and excited to use OpenAI’s unique resources.
  • 2+ years of research engineering experience and proficiency in Python or similar languages.
  • Deeply curious.

Skills

Mechanistic InterpretabilityDeep LearningPythonMachine LearningAi SafetyResearch EngineeringPyTorchTransformer ModelsNeuroscienceLLMs

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