Research Engineer, Production Model Post Training

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Post-Training team improves production models via post-training processes that enhance capabilities, alignment, and safety. As a Research Engineer on this team, you will train base models through the full post-training stack to deliver production Claude models used by customers. You will work at the intersection of research and production engineering, implementing, scaling, and improving post-training techniques such as Constitutional AI and RLHF, and improving the safety and capabilities of production models.

Responsibilities

• Implement and optimize post-training techniques at scale on frontier models (e.g., Constitutional AI, RLHF, and other alignment methodologies)
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training
• Potentially respond to incidents on short notice (including weekends)

Requirements

• Strong software engineering skills with experience building complex ML systems
• Proficiency in Python (interviews are conducted in Python)
• Experience with training, fine-tuning, or evaluating large language models
• Comfortable working with large-scale distributed systems and high-performance computing
• Experience building and operating robust model training and evaluation pipelines
• Ability to analyze and debug model training processes and model behavior
• Ability to balance research exploration with engineering rigor and operational reliability
• Bachelor's degree in a related field or equivalent experience (minimum requirement)

Strong candidates may also

• Have direct experience with LLMs and frontier AI systems
• Have a keen interest in AI safety and responsible deployment

Benefits & Compensation

• Annual base salary range: $315,000 - $340,000 USD
• Total compensation for full-time employees may include equity, benefits, and possible incentive compensation
• Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space

Logistics

• Locations: San Francisco, CA; New York City, NY; Seattle, WA (U.S. offices)
• Location-based hybrid policy: staff are expected to be in one of the offices at least 25% of the time (some roles may require more)
• Interviews are conducted in Python
• Role may require on-call / incident response work
• Visa sponsorship: Anthropic does sponsor visas, but sponsorship success is not guaranteed for every role
• Education: minimum of a Bachelor’s degree in a related field or equivalent experience

How we work / Culture

• Collaborative research-focused environment working on large-scale, high-impact AI research and engineering
• Emphasis on communication, reproducibility, and operational reliability

Application notes

• Applicants are encouraged to apply even if they do not meet every qualification listed
• Candidates should provide a resume or LinkedIn profile