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Researcher, Recursive Self-Improvement Safety

San Francisco💼 Full-time🗓 2026-08-07 → 2026-09-26

Core

Designing and implementing control measures, risk assessments, and monitoring systems to mitigate future misalignment risks in AI systems capable of recursive self-improvement.

Role type

Senior IC AI safety researcher (recursive self-improvement safety)

Builds

Pre-deployment risk-assessment tools, control measures, automated auditing systems, and safety pipelines for production models.

Domain

AI Safety / Machine Learning / Recursive Self-Improvement

Deliverable

production ML models

Required skills

hypothesis-driven research, strategic prioritization in weak feedback loop domains, rapid prototyping, technical execution, risk assessment design, automated auditing, model behavior science, coordination and verification of safety agreements, blindspot identification in mitigation areas

Preferred skills

experience in ML research, AI alignment, AI verification, training model organisms of misbehavior, training interventions for safety-relevant capabilities

Technologies

production traffic analysis, Chain-of-Thought monitoring, reward hacking detection, sandbagging detection, scheming detection, automated auditing frameworks

Responsibilities

Prioritize concrete directions for preparing against future misalignment threats; execute rapid prototyping of safety interventions; build and iterate components for safety pipelines; secure buy-in and communicate work clearly; collaborate with or manage staff to scale problem-solving efforts

Seniority

Senior, hands-on IC

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