Researcher, Misalignment Monitoring Lead
$380k - $500k • Remote • San Francisco • FullTime
Posted 1d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
OpenAI's Safety Research organization is seeking a senior researcher to lead technical work on misalignment monitoring for frontier AI systems. This role involves developing methods to evaluate AI monitors, understanding their limitations, and improving our ability to reliably detect and stop concerning model behavior. You will set research priorities, design rigorous evaluations, investigate monitoring failures, and develop approaches for stress-testing and improving monitoring systems, with a key focus on understanding monitor limitations as models evolve. The position combines research leadership with hands-on technical execution, translating research findings into practical improvements for OpenAI's safety systems.
Responsibilities
- Lead research and technical direction for evaluating and improving misalignment monitoring of frontier AI systems.
- Design and execute rigorous evaluations to measure monitor effectiveness, identify failure modes, and assess reliability.
- Develop methods to stress-test and red-team monitors, identifying behaviors that evade detection or expose weaknesses.
- Investigate monitoring failures, such as false positives and missed detections, to improve accuracy and usefulness.
- Build scalable evaluation frameworks and experimental tools for ongoing monitoring performance measurement.
- Translate research findings into actionable improvements for monitoring systems and safety decisions.
- Establish research priorities and guide technical execution, balancing foundational research with practical needs.
Requirements
- Strong background in machine learning research, particularly in model evaluations, AI safety, alignment, or robustness.
- Demonstrated ability to lead technically challenging research projects from inception to delivery.
- Strong experimental judgment and ability to design rigorous, reproducible evaluations.
- Hands-on experience building or evaluating machine learning systems, including large language models or frontier AI systems.
- Comfort working on open-ended research problems with unclear methodologies or success criteria.
- Ability to combine strong research instincts with practical engineering skills for independent experiment building and analysis.
- Clear communication of technical findings and enjoyment of cross-team collaboration.
- Motivation by OpenAI's mission and the challenge of developing oversight mechanisms for advanced AI.