模型政策经理
Model Policy Manager
关于团队
我们的安全系统 https://openai.com/safety/safety-systems 团队处于 OpenAI 构建和部署安全人工智能（AGI）使命的最前沿，推动我们对人工智能安全的承诺，并培养信任和透明的文化。
在安全系统团队中，模型政策团队确保模型行为符合期望的人类价值观和规范。我们通过基于数据的快速政策分类迭代，以及定义基础模型推理安全能力的评估标准，与模型共同设计政策并为模型设计政策。
关于职位
如果你有与此工作相关的特定专业知识或专长，请在申请中通过简历、求职信或申请说明注明。
前沿人工智能系统正在扩展人们在各个领域的能力，既带来了巨大的机遇，也带来了复杂的安全问题：模型何时应该提供帮助，何时应该拒绝，我们如何让这些界限足够清晰以进行训练、评估和执行？
在这个职位中，你将帮助定义 OpenAI 模型在高风险或高模糊性情境中的行为，例如代理系统、多模态系统、用户安全、隐私以及其他新兴风险领域。
这是一个适合能够跨越陌生主题、从第一性原理进行推理，并将模糊性转化为实际模型行为的人的职位。你将与研究、工程、产品、准备和运营团队紧密合作，制定技术基础、可衡量且对现实世界风险有响应的政策。
你的职责包括：
- 在安全相关领域设计和维护模型政策，包括双重用途、代理性和新兴前沿风险领域。
- 将风险和伤害模型转化为清晰的行为规范、评估标准、评分指南和系统级防护措施。
- 定义人工智能有益用途与可能实质性促成伤害、剥削、滥用或不安全结果的帮助之间的实际边界。
- 构建支持模型训练、评估和部署的政策文档。与安全研究人员、工程师、产品团队和其他利益相关者合作，将政策转化为可扩展的模型行为和可衡量的防护措施。
- 利用红队测试结果、部署数据、模型故障、过度拒绝、拒绝不足和模糊边缘案例，持续改进政策和评估质量。
- 识别前沿人工智能系统可能带来新安全挑战的新能力领域。
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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.
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/
Workplace & Location
This role is based in our San Francisco office. We do encourage you to apply even if you prefer a different work location as factors may change over time.
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.
Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, a private outdoor space for working in the sun or socializing, nap rooms, private bike storage, and more.
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. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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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.