Researcher, Recursive Self-Improvement Safety
full-time
mid
Posted 4 months ago
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About this role
ABOUT THE TEAM
Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity.
Our work involves:
- Tracking and prediction. Monitoring https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/ and predicting the evolving misalignment propensities and capabilities of frontier AI systems.
- Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future.
- Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework, and partnering with other staff to achieve these targets.
This is urgent, fast-paced work that has far-reaching implications for the company and for society.
ABOUT THE ROLE
Preparedness is hiring strong technical executors to support preparations for recursive self-improvement. This work relies on reasoning about problems 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://alignment.openai.com/prod-evals/, control measures, RSI-relevant training interventions, and turning one’s technical work into established institutional practices.
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.
IN THIS ROLE, YOU WILL:
- 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 security threats” into a much more concrete direction (e.g. “implement monitors for data poisoning”) – prioritizing the work that is most useful to start right now.
- Execute quickly, building scrappy prototypes, and then improving them iteratively until they become established components of our safety pipelines.
- Secure buy-in from other staff at OpenAI when necessary, and communicate your work clearly.
- Collaborate with or manage other staff as needed, since we might need to rapidly scale to tackle these problems quickly.
YOU MIGHT THRIVE IN THIS ROLE IF YOU:
- Are an exceptional technical executor.
- Have strong strategic and research taste: you can prioritize effectively in domains with weak feedback loops.
- Are passionate about mitigating the risks associated with recursive self-improvement.
- Are driven by a desire to do whatever work most positively impacts the future of AI development.
- Bonus: you have already done work in one of the domains listed above (ML research, AI alignment, AI verification etc).
About OpenAI
OpenAI is an AI research and deployment company
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