可解释性研究员

About the Team The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. About the Role 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. In this role, you will: • 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.

You might thrive in this role if you: • Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s 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.

• Hold a Ph.D. or have research experience in computer science, machine learning, or a related field.

• Thrive in environments involving large-scale AI systems,

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. In this role, you will: • 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.

You might thrive in this role if you: • Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s 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.

• Hold a Ph.D. or have research experience in computer science, machine learning, or a related field.

• Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area.

• Possess 2+ years of research engineering experience and proficiency in Python or similar languages.

• Are deeply curious.

About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.