Senior Researcher - Safety Systems, Misalignment Research
- Worst-Case Demonstrations - Craft compelling, reality-anchored demos that reveal how AI systems can go wrong. We focus especially on high importance cases where misaligned AGI could pursue goals at odds with human well being.
- Adversarial & Frontier Safety Evaluations - Transform those demos into rigorous, repeatable evaluations that measure dangerous capabilities and residual risks. Topics of interest include deceptive behavior, scheming, reward hacking, deception in reasoning, and power-seeking, along with other related areas.
- System-Level Stress Testing - Build automated infrastructure to probe entire product stacks, assessing end-to-end robustness under extreme conditions. We treat misalignment as an evolving adversary, escalating tests until we find breaking points even as systems continue to improve.
- Alignment Stress-Testing Research - Investigate why mitigations break, publishing insights that shape strategy and next-generation safeguards. We collaborate with other labs when useful and actively share misalignment findings to accelerate collective progress.
- Design and implement worst-case demonstrations that make AGI alignment risks concrete for stakeholders, focused on high stakes use cases described above.
- Develop adversarial and system-level evaluations grounded in those demonstrations, driving adoption across OpenAI.
- Create automated tools and infrastructure to scale automated red-teaming and stress testing.
- Conduct research on failure modes of alignment techniques and propose improvements.
- Publish influential internal or external papers that shift safety strategy or industry practice. We aim to concretely reduce existential AI risk.
- Partner with engineering, research, policy, and legal teams to integrate findings into product safeguards and governance processes.
- Mentor engineers and researchers, fostering a culture of rigorous, impact-oriented safety work.
- Already are thinking about these problems night and day, and share our mission to build safe, universally beneficial AGI and align with the OpenAI Charter.
- Have 4+ years of experience in AI red-teaming, security research, adversarial ML, or related safety fields.
- Possess a strong research track record-publications, open-source projects, or high-impact internal work-demonstrating creativity in uncovering and exploiting system weaknesses.
- Are fluent in modern ML / AI techniques and comfortable hacking on large-scale codebases and evaluation infrastructure.
- Communicate clearly with both technical and non-technical audiences, translating complex findings into actionable recommendations.
- Enjoy collaboration and can drive cross-functional projects that span research, engineering, and policy.
- Hold a Ph.D., master's degree, or equivalent experience in computer science, machine learning, security, or a related discipline (nice to have but not required).
- A chance to shape safety practices at the frontier of AGI. Your work will directly lower the changes of catastrophic misalignment.
- Access to cutting-edge models, tooling, and compute resources.
- A highly collaborative, mission-driven environment with world-class colleagues.
- Competitive compensation, equity, and benefits.
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