Research Engineer, Reward Models

Details

Anthropic’s Reward Modeling team is developing techniques to teach AI systems to understand and embody human values while pushing forward AI capabilities. This expression-of-interest posting is for engineers who want to work on reward modeling for large language models and frontier AI research. Note: interviews for this role are conducted in Python. Headcount for 2025 is filled; applications submitted now will be reviewed as the team grows.

Responsibilities

• Help implement novel reward modeling architectures and techniques
• Optimize training pipelines
• Build and optimize data pipelines
• Collaborate across teams to integrate reward modeling advances into production systems
• Communicate engineering progress through internal documentation and potential publications

Requirements

• Strong engineering background in machine learning with demonstrable expertise in preference learning, reinforcement learning, deep learning, or related areas
• Proficiency in Python (required) and experience with deep learning frameworks
• Experience with distributed computing
• Familiarity with modern LLM architectures and alignment techniques
• Experience improving model training pipelines and building data pipelines
• Comfortable with the experimental nature of frontier AI research and able to implement research ideas
• Ability to clearly communicate complex technical concepts and research findings
• Deep interest in AI alignment and safety
• Education: at least a Bachelor’s degree in a related field or equivalent experience

Notes from the posting:

• Experience with reward models is not required; experience with LLMs or other large models is a significant plus
• The team welcomes candidates at various experience levels, with a preference for senior engineers
• Interviews for this role are conducted in Python

Compensation

• Annual base salary: $315,000 - $340,000 USD
• The total compensation package for full-time employees includes equity, benefits, and may include incentive compensation

Logistics & Policy

• Locations: San Francisco, CA; New York City, NY; Seattle, WA (United States)
• Location-based hybrid policy: currently expect all staff to be in one of our offices at least 25% of the time
• Visa sponsorship: Anthropic does sponsor visas in many cases and retains an immigration lawyer to assist

Benefits / Why Anthropic

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours and office space for collaboration
• Emphasis on large-scale, collaborative research and frequent research discussions

Application details

• This is an expression-of-interest form; you may not hear back immediately
• Applicants are asked for resume or LinkedIn, optional cover letter, GitHub, publications, and answers about availability and relocation
• Guidance on candidates' AI usage is provided in Anthropic's candidate AI policy