Researcher, Misalignment Monitoring Lead

Compensation

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this position is $380K - $500K per year, with generous equity, performance-related bonuses, and the following benefits:

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
• 401(k) retirement plan with employer match
• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend to fuel your professional growth
• Daily meals in our offices, and meal delivery credits as eligible
• Relocation support for eligible employees
• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

OpenAI's Safety Research organization works to ensure that our most capable AI models can be deployed safely and responsibly. We focus on advancing the research and evaluation methods needed to understand model behavior and ensure that monitoring systems remain effective as model capabilities evolve.

About the Role

We are looking for a senior researcher to lead technical work on misalignment monitoring for frontier AI systems. You will develop methods to evaluate the effectiveness of AI monitors, understand their limitations, and improve our ability to detect and stop concerning model behavior reliably.

Responsibilities

• Lead the research and technical direction for evaluating and improving the misalignment monitoring of frontier AI systems.
• Design and execute rigorous evaluations that measure monitor effectiveness, identify failure modes, and assess the reliability of monitoring signals.
• Develop methods to stress-test and red-team monitors, including identifying behaviors that evade detection or expose weaknesses in existing approaches.
• Investigate false positives, missed detections, and other monitoring failures to improve the accuracy and usefulness of safety evaluations.
• Build scalable evaluation frameworks and experimental tools that enable ongoing measurement of monitoring performance as model capabilities evolve.
• Translate research findings into actionable improvements, working with partner teams to strengthen monitoring systems and inform broader safety decisions.
• Establish research priorities and guide technical execution, balancing foundational research questions with practical deployment needs.

Requirements

• Strong background in machine learning research, particularly in model evaluations, AI safety, alignment, robustness, or related areas.
• Demonstrated ability to lead technically challenging research projects, from identifying important questions through designing experiments and delivering results.
• Strong experimental judgment and understanding of how to design evaluations that are rigorous, reproducible, and difficult to game.
• Hands-on experience building or evaluating machine learning systems, including working with large language models or other frontier AI systems.
• Enjoy investigating complex failure modes and developing methods to distinguish meaningful safety signals from misleading measurements.
• Comfortable working on open-ended research problems where the right methodology or success criteria may not be obvious at the outset.
• Combine strong research instincts with practical engineering ability and can independently build experiments, analyze results, and iterate quickly.
• Communicate technical findings clearly and enjoy collaborating across research, engineering, and safety teams.
• Motivated by OpenAI's mission and the challenge of developing reliable oversight mechanisms for increasingly capable AI systems.

Nice to Have

• Experience with AI monitoring, automated evaluations, adversarial testing, or red-teaming.
• Research experience in scalable oversight, AI control, model behavior analysis, or interpretability.
• Experience developing monitoring or evaluation systems that are used in real-world deployments.
• A track record of technical research leadership, including mentoring researchers or coordinating cross-functional research initiatives.