Researcher, Recursive Self-Improvement Safety

OpenAI, San Francisco +1

The role

Preparedness is hiring strong technical executors to support preparations for accelerated AI development, which may culminate in recursive self-improvement. This work relies on anticipating misalignment risks that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic.

The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment https://openai.com/index/deployment-simulation/, control measures https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/, RSI-relevant training interventions, and turning one’s technical work into established institutional practices and external-facing communications.

What you will do

Carefully consider the problems OpenAI might face in the future and how to prepare for them.
Turn an open-ended objective like “prepare for future misalignment threats” into a much more concrete direction (e.g. “stress-test monitors for scheming”) – prioritizing the work that is most useful to start right now.

All jobs

Researcher, Recursive Self-Improvement Safety

OpenAI, San Francisco +1

The role

What you will do

Carefully consider the problems OpenAI might face in the future and how to prepare for them.
Turn an open-ended objective like “prepare for future misalignment threats” into a much more concrete direction (e.g. “stress-test monitors for scheming”) – prioritizing the work that is most useful to start right now.

Below is a subset of our focus areas

Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones.
Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to sift through large swaths of production traffic https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/ to find the most egregious misalignments, and reliably elicit tail risks before deployment.
Rigorous monitorability: Rigorous testing and red-teaming of our measurements of model misbehavior related to loss-of-control (e.g. reward hacking, sandbagging, scheming). This includes better https://arxiv.org/abs/2603.05706 understanding https://alignment.openai.com/accidental-cot-grading/ monitorability https://arxiv.org/abs/2512.18311, and e.g. preparing for potential losses of Chain-of-Thought monitorability.
Model behavior science: Design experiments and evaluations to understand the extent to which models are problematically misaligned, or their safety-relevant capabilities lag behind dangerous capabilities. This may include training model organisms of misbehavior for behaviors not currently present in production, or training interventions to increase safety-relevant capabilities.
Coordination and verification: Prototype technical mechanisms for verifying compliance with potential future AI safety agreements.
AI R&D risk measurement: Track progress toward automation of technical staff to inform OpenAI’s near-term investments in alignment and security.
Maintaining and strengthening RSI safety cases: We’re especially interested in identifying and addressing blindspots of mitigation areas which we may have missed.

Generally, our team alternates between performing rigorous hypothesis-driven research and turning our insights into interventions or control systems which impact production models, with occasional support of engineering teams.

Researcher, Recursive Self-Improvement Safety

The role

What you will do

Researcher, Recursive Self-Improvement Safety

The role

What you will do

What you need

About the team

Below is a subset of our focus areas

About OpenAI

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