Researcher, Alignment CoT Monitorability

Details

About the Team

The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. The team studies how to measure monitorability, which training mechanisms affect monitorability, and speculative methods to improve monitorability. While the team mostly focuses on chain-of-thought (CoT) monitorability at the moment, it cares more generally about any form of monitorability, auditing methods, and improving alignment.

The team was the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today their monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues surfaced are used to help improve reward functions, environments, and other training pipeline components (without directly training against a CoT monitor).

Work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research. The team cares most about monitorability where the stakes are high and about preserving useful oversight signals as models become more capable.

About the Role

We are looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work.

As a researcher on the Alignment team, you will design and run experiments that improve understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs.

This role is especially well suited for someone who can move from an ambiguous model-behavior question to a concrete experimental setup: formulate the hypothesis, build the evaluation or intervention, run the experiment, analyze the result, and decide what the evidence supports. This role is based in San Francisco, CA. The team uses a hybrid work model of 3 days in the office per week and offers relocation assistance to new employees.

Responsibilities

• Design and run empirical studies of chain-of-thought monitorability across frontier reasoning models and training settings.
• Build evaluations that measure whether monitors can reliably predict properties of interest, including high-stakes forms of misbehavior.
• Investigate how pre-training, synthetic data, mid-training, post-training, reinforcement learning, and other interventions improve or degrade monitorability.
• Analyze model behavior and turn observations from monitoring into hypotheses, experiments, and recommendations.
• Translate research findings into practical monitoring and oversight approaches that can inform real training runs.
• Collaborate with researchers and engineers across model training, alignment evaluations, monitoring, and frontier-risk work.
• Produce externally publishable research when results advance the broader science of alignment.

Requirements / Qualifications

• Strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs.
• Deep curiosity and interest in alignment, model behavior, and interpretability.
• Experience or depth in alignment, interpretability, empirical ML, or adjacent research areas.
• Ability to turn ambiguous research questions into measurable experiments and to follow the evidence when results are subtle or noisy.
• Comfortable moving between research ideation and engineering execution; able to design experiments, run them, and analyze results.
• Ability to operate with high independence while collaborating closely across research and engineering teams.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. OpenAI pushes the boundaries of AI capabilities and seeks to safely deploy them through its products. The company is an equal opportunity employer and is committed to providing reasonable accommodations to applicants with disabilities.

Additional notes in the posting: background checks will be administered in accordance with applicable law. The company provides relocation support for eligible employees and other benefits described during the hiring process.