Hybrid Senior Research Scientist, Reward Models

at Anthropic

• Job title: Senior Research Scientist, Reward Models
• Job type: Full Time
• Experience level: Senior
• Salary: $340,000 - $425,000 per year
• Degree requirement: Bachelor's Degree
• Location requirements: Hybrid, San Francisco, United States

About the role

• Senior Research Scientist leading research efforts on reward models for AI. Shaping how models understand and optimize for human preferences with a focus on AI safety and capability.

Responsibilities

• Lead research on novel reward model architectures and training approaches for RLHF
• Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability
• Research techniques to detect, characterize, and mitigate reward hacking and specification gaming
• Design experiments to understand reward model generalization, robustness, and failure modes
• Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines
• Contribute to research publications, blog posts, and internal documentation
• Mentor other researchers and help build institutional knowledge around reward modeling

Requirements

• A track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning
• Experience training and evaluating reward models for large language models
• Comfortable designing and running large-scale experiments with significant computational resources
• Work effectively across research and engineering, iterating quickly while maintaining scientific rigor
• Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences
• Care deeply about building AI systems that are both highly capable and safe.
• Strong candidates may also have published research on reward modeling, preference learning, or RLHF
• Experience with LLM-as-judge approaches including calibration and reliability challenges
• Worked on reward hacking, specification gaming, or related robustness problems
• Experience with constitutional AI, debate, or other scalable oversight approaches
• Contributed to production ML systems at scale
• Familiarity with interpretability techniques as applied to understanding reward model behavior.

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours