Model Policy Manager
Remote • San Francisco • FullTime
Posted 25d ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. This senior role will shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior, sitting at the intersection of biosecurity expertise, AI safety research, and policy design. The goal is to ensure that frontier AI systems can support beneficial life sciences research while reducing the risk of misuse.
Responsibilities
- Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios.
- Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safety monitoring systems.
- Translate biosecurity and chemical security expertise into actionable model behavior, working closely with research and engineering teams to operationalize policy in training and evaluation pipelines.
- Develop broad subject matter expertise while maintaining agility across topics.
- Identify emerging risk vectors where frontier AI capabilities could lower barriers to harmful activity and develop mitigation strategies.
- Engage with internal and external subject-matter experts in biosecurity, biodefense, and chemical safety to ensure policies reflect real-world risk landscapes.
Requirements
- Strong domain expertise in chemistry, biology, biosecurity, or related fields and motivation to translate that expertise into principled, operational policies that scale to Frontier AI systems.
- Experience researching LLMs, ML, AI, tech policy, moral reasoning, and/or classification problems.
- Extensive experience defining, refining and enforcing policies for ML models across training, evaluation, and deployment.
- Comfort navigating ambiguous, high-stakes problem spaces, balancing risk reduction with the benefits of scientific openness and innovation.
- Ability to reason about benefits and risks of open-ended problem spaces, generate novel approaches under ambiguity, and take full ownership of end-to-end solutions.
- Experience working at the intersection of science, policy, or emerging technology, such as in life sciences research, national security, risk analysis, technology policy, or AI safety.
Benefits
- Hybrid work model (3 days in office per week)
- Relocation assistance to new employees