About the job
OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI.
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.
Qualifications
Minimum
Hold a Ph.D. or have research experience in computer science, machine learning, or a related field.
Possess 2+ years of research engineering experience and proficiency in Python or similar languages.
Preferred
Are excited about OpenAI’s mission https://openai.com/about/ of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter https://openai.com/charter/.
Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI.
Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines.
Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area.
Are deeply curious.