Research Engineer, Production Model Post Training

Research Engineer, Production Model Post Training

Responsible for training our base models through the complete post‑training stack to deliver the production Claude models users interact with.

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and society. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Anthropic’s production models undergo sophisticated post‑training processes to enhance capabilities, alignment, and safety. As a Research Engineer on our Post‑Training team, you will implement and optimize post‑training techniques at scale, 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, and help establish best practices for reliable, reproducible model post‑training.

Note:

All interviews are conducted in Python. This role may require responding to incidents on short notice, including on weekends.

• Implement and optimize post‑training techniques at scale on frontier models
• 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

• Thrive in controlled chaos and are energized, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time‑sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large‑scale distributed systems and high‑performance computing
• Have experience with training, fine‑tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analyzing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast‑moving research environments

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

Annual Salary: $315,000—$340,000 USD
Full‑time employees receive equity, benefits, and may include incentive compensation.

Education requirements: Bachelor’s degree in a related field or equivalent experience.
Location‑based hybrid policy: Staff expected to be in one of our offices at least 25% of the time; some roles may require more in‑office presence.
Visa sponsorship: We sponsor visas and will make every reasonable effort to assist with immigration.
Candidate encouragement: We welcome candidates at various experience levels, with a preference for senior engineers who have hands‑on experience with frontier AI systems. We encourage you to apply even if you do not meet every single qualification.

Guidance on Candidates' AI Usage:
Learn about our policy for using AI in our application process.