Research Scientist, Machine Learning

About the team

The Policy Research team at OpenAI is responsible for understanding our company’s current and potential impact on the world, and using that understanding to recommend the best possible policies at OpenAI and elsewhere (“policies” are defined broadly to include laws, safety requirements, industry norms, etc.). Team members have backgrounds in a wide variety of disciplines, including computer science and engineering, law, philosophy, economics, political science, and more, and we use a wide variety of quantitative and qualitative methods to measure, forecast, and analyze OpenAI’s impacts.

About the role

We’re seeking an experienced machine learning researcher to shape and lead the ML research agenda for trustworthy AI. 

This is an opportunity to pioneer and prototype new approaches for testing and evaluating the most advanced AI systems – and to harness the most advanced AI systems to do so. The role will include research on the development of novel evaluation methods and interventions for things like dangerous model capabilities and existential risks, fairness and representation, as well as untruthful, hallucinatory, or otherwise undesired model behavior. 

If you enjoy tackling deep questions in ML research, thrive in roles where ambitious entrepreneurial pursuit of open-ended goals is rewarded, and are strongly motivated to contribute to the roll-out of advanced general AI systems going well, you will find our work here uniquely challenging and rewarding. This role reports to our Trustworthy AI lead.

This role is based in our San Francisco HQ. We offer relocation assistance to new employees.

In addition, you’ll:

• Research upstream interventions at the level of training data, pre-training, and training
• Research and prototype novel evaluation methods in areas such as dangerous model capabilities and existential risks, fairness and representation, as well as untruthful, hallucinatory, or otherwise undesired model behavior. 
• Work with downstream product and infrastructure teams to build and scale effective tools for responsible deployment
• Develop and mentor ML Researchers on the Deployment Planning team
• Architect and develop interventions that improve real world impact

We Expect You To:

• Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects
• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects
• Have experience developing novel techniques for ML model measurement and mitigation
• Have experience in research mentorship, leading project teams, and setting technical direction
• Be comfortable working cross functionally across both research and product teams

Nice to Haves:

• Past experience in interdisciplinary research collaborations
• Past experience in creating high-performance implementations of deep learning algorithms