Model Policy Manager

About the Team Our Safety Systems https://openai.com/safety/safety-systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role If you have a specific expertise or speciality related to this work, please note it in your application via your resume, cover letter or application note. Frontier AI systems are expanding what people can do across domains, creating both enormous opportunities and difficult safety questions: when should a model help, when should it refuse, and how do we make those boundaries clear enough to train, evaluate, and enforce? In this role, you will help define how OpenAI’s models should behave in high-risk or high-ambiguity contexts, such as agentic systems, multimodal systems, user safety, privacy, and other emerging risk domains. This is an ideal role for someone who can move across unfamiliar topics, reason from first principles, and turn ambiguity into practical model behavior. You will work closely with research, engineering, product, preparedness, and operations teams to build policies that are technically grounded, measurable, and responsive to real-world risk. This role is based in our San Francisco office. We offer relocation support to new employees, and we use a hybrid model: three days in the office per week with optional work from home on Thursdays and Fridays. Your Responsibilities: - Design and maintain model policies across safety-relevant domains, including dual-use, agentic, and emerging frontier-risk areas. - Translate risk and harm models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level safeguards. - Define practical boundaries between beneficial uses of AI and assistance that could materially enable harm, exploitation, misuse, or unsafe outcomes. - Build policy artifacts that support model training, evaluation, and deployment.Partner with safety researchers, engineers, product teams, and other stakeholders to operationalize policy into scalable model behavior and measurable safeguards. - Use red-teaming results, deployment data, model failures, over-refusals, under-refusals, and ambiguous edge cases to improve policy and evaluation quality over time. - Identify emerging capability areas where frontier AI systems could create new safety challenges or lower barriers to harm. - Study real-world deployments to identify where model behavior succeeds, fails, or drifts from the intended safety posture. - Combine longer-horizon safety research with hands-on launch and deployment work. - Contribute to system cards, safety reports, policy documentation, launch reviews, and external communications on OpenAI's approach to model safety and risk mitigation. - Design and run human data campaigns, including gold set construction, labeling guidance, calibration, adjudication, and eval coverage analysis, to ensure policies can be reliably measured and improved. We’re seeking someone who: - Has strong judgment about how advanced AI systems may affect real-world risk, especially in ambiguous, fast-moving, or high-impact areas. - Has experience building or applying policies, taxonomies, harm models, threat models, or risk frameworks for complex technical, social, or adversarial systems. - Can move across domains without needing to be the deepest subject-matter expert in every area, while knowing when to seek expert input. - Can turn fuzzy questions into structured policy frameworks, evaluation criteria, operational guidance, and enforceable model behavior. - Is comfortable using empirical evidence, including evaluations, red-teaming results, deployment observations, and model failure modes, to inform policy decisions. - Thinks in systems across policy, data, graders, classifiers, training, deployment safeguards, measurement, monitoring, and escalation workflows. - Has technical judgment about what model behavior can realistically be trained, measured, evaluated, and enforced at scale. - Works well across research, engineering, product, policy, domain experts, and operational teams. - Writes clearly about complex tradeoffs where safety, user value, and implementation constraints all matter. - Takes a pragmatic approach to safety, focused on reducing real-world risk while preserving legitimate, beneficial, and socially valuable uses of AI. - Enjoys fast-paced, collaborative research environments where priorities shift as models, evidence, and risks change. - Stays grounded in implementation details, empirical results, and what can actually be trained or measured. Our relevant publications: - Accelerating the cyber defense ecosystem that protects us all https://openai.com/index/accelerating-cyber-defense-ecosystem/ - Trusted Access https://openai.com/index/scaling-trusted-access-for-cyber-defense/ - Safety at every step https://openai.com/safety/ - Safety evaluations hub https://openai.com/safety/evaluations-hub/ - OpenAI GPT5.5 System Card https://openai.com/index/gpt-5-5-system-card/ - Improving Model Safety Behavior with Rule-Based Rewards https://openai.com/index/improving-model-safety-behavior-with-rule-based-rewards/ - OpenAI Model Spec https://openai.com/index/introducing-the-model-spec/ 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 https://cdn.openai.com/policies/eeo-policy-statement.pdf. 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. 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