At a glance
Shape safety policies for OpenAI’s multimodal frontier models, translating threats and harms into measurable behaviors, evaluations, safeguards, and training artifacts that support responsible deployment.
Summarized by AI from the original posting
What you'll do
- Design and maintain policies for audio, image, video, and omni-modal model behavior
- Translate theories of harm and threat models into policies, evaluation criteria, grading guidance, and safeguards
- Identify safety regressions and failure patterns
- Develop policy artifacts for model training, evaluation, and deployment
- Partner with AI researchers, domain experts, and product teams to operationalize policy into measurable model behavior
Requirements
- 01Strong judgment about real-world risks of advanced multimodal AI systems
- 02Experience translating ambiguous safety questions into data-driven policies and measurable evaluation criteria
- 03Technical fluency with model behavior, training, evaluation, and supervision at scale
- 04Hands-on experience analyzing model data, evaluation results, and failure patterns
- 05Experience driving consensus and action in ambiguous environments
Perks
Skills
Full description
About the Team
Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations.
Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. Our relevant publications include:
About the Role
We are hiring a Model Policy Manager to focus on the safety of multimodal models. In this role, you will shape how OpenAI identifies, evaluates, and addresses risks in multimodal AI models - such as GPT-Live and ChatGPT Images - as well as multimodal capabilities in frontier AI models.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Design and maintain model policies for audio, image, video, and omni-modal behavior.
Translate theories of harm and threat models into behavioral safety policies, evaluation criteria, grading guidance, and safeguards.
Identify and analyze safety regressions and failure patterns to identify gaps in existing policies and inform policy iteration.
Develop policy artifacts that support model training, evaluation, and deployment, including behavior instructions, human-data campaigns, golden sets, and evaluations.
Partner with AI researchers, domain experts, and product teams to operationalize policy into measurable model behavior.
You might thrive in this role if you:
Have strong judgment about the real-world risks of advanced multimodal AI systems.
Possess experience turning ambiguous safety questions into clear data-driven policies, behavioral boundaries, and measurable evaluation criteria.
Treat policy as an end-to-end, measurable system by testing whether it produces the intended model behavior and diagnosing gaps across policy, data, graders, and safeguards.
Leverage strong technical judgement to design policies around model behavior that can realistically be trained, measured, and supervised at scale.
Demonstrate strong technical fluency and uses AI tools to accelerate policy development, evaluate model behavior, analyze failure patterns, and turn findings into actionable improvements.
Are comfortable working hands-on with model data and evaluation results, including inspecting examples, analyzing failure patterns, assessing data quality, and distinguishing policy failures from grader, model, or system failures.
Enjoy fast-paced, collaborative research environments where priorities shift as models, evidence, and risks change.
Take a pragmatic, evidence-driven approach to reducing risk while preserving beneficial uses of AI.
Have hands-on experience driving consensus and action in ambiguous spaces.
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.
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Compensation: $266K - $335K