apolloresearch - Apollo Research - Research Scientist/Engineer (Science of Scheming)
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Requirements
• Fast-paced empirical research: Designing and executing experiments to speed up iteration cycles; excellence in this area. • Conceptual insights about scheming: Familiarity with relevant literature on AI scheming, turning vague concepts into concrete experiment proposals. • Software engineering skills (Python): Strong software engineering abilities for effective execution of work using Python stack. • Intense interest in AI progress: Staying up to date on the latest model releases and continuously tinkering with new workflows; fascination by AI cognition, actively trying to understand how they think. • Experience RL-training LLMs (reinforcement learning): Hands-on experience in training large language models via reinforcement learning techniques. • Strong analytical skills: Background working on fields such as scaling laws in LLMs, statistical physics, dynamical systems, applied statistics; comfortable building mathematical models of empirical phenomena and understanding quantitative aspects related to AI scheming risks evolution with model capability scale.
Responsibilities
• Collaborate with leading AI developers to impact the construction and deployment of capable AI systems through research collaborations. • Study RL dynamics related to reward-seeking behavior, evaluation awareness, and misaligned preferences; design and train model organisms for scaling insights into frontier systems. • Work on developing novel empirical foundations predicting how scheming risks evolve as models scale in capability (Scaling laws of scheming). • Develop new evaluation techniques with the potential to be applied to highly evaluation aware AI models. • Investigate patterns in reasoning processes within frontier AI systems that have not been observed before, focusing on aspects related to cognition and behavioral insights.
Benefits
• Equity options mentioned as part of the benefits package • Paid Time Off (PTO) is included in the compensation plan • Insurance coverage provided to employees • Remote work options offered, allowing for flexibility in working location
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