Description
Anthropic's mission is to create reliable, interpretable, and steerable AI systems.
We're looking for a Research Scientist to focus on measuring and understanding recursive-self-improvement in large models.
Responsibilities:
- Identify signals that track AI R&D acceleration and design evaluations to measure them
- Build quantitative models of capability growth and self-improvement dynamics
- Run experiments and evaluations to test hypotheses about automation and capability
- Make research bets and own the outcome
- Write assessments of measurements for internal decision-makers and public reporting
- Collaborate with pretraining, RL, economic research, and policy teams
Requirements:
- Hands-on research experience with large language models
- Strong quantitative instincts and comfort with quantitative modeling
- Experience in forecasting and publishing AI forecasting scenarios
- Ability to design evaluations and defend methodologies
- Clear writing and calibration of conclusions
- Motivation by impact and focus on graded assessments
- Care about AI safety and rapid capability growth
Strong candidates may also have:
- Trained or RL'd frontier models hands-on
- Experience with scaling laws, capability forecasting, or emergent-capability studies
- A physics, applied-math, or similarly quantitative background
- Written system card sections, capability reports, or methodology documents
- Experience supervising and correcting AI-written code
The annual compensation range for this role is $350,000-$850,000 USD.
Logistics:
- Minimum education: Bachelor's degree or equivalent
- Required field of study: Relevant to the role
- Minimum years of experience: Correlates with internal job level requirements
- Location-based hybrid policy: 25% office time
- Visa sponsorship: Available
This listing is enriched and indexed by YubHub. To apply, use the employer's original posting:
https://job-boards.greenhouse.io/anthropic/jobs/5370669008