Research Engineer (Production Model Post Training)

• As a Research Engineer on our Post-Training team, you’ll develop and optimize the systems that transform our base models into the refined Claude models that users interact with
• You’ll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies
• Your work will directly impact the quality, safety, and capabilities of our production models
• Implement and optimize post-training techniques at scale on frontier models
• 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

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents

• Inclusive fertility benefits via Carrot Fertility

• 22 weeks of paid parental leave

• Flexible paid time off and absence policies

• Mental health support for you and your dependents

• Competitive salary and equity packages

• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant

• Retirement plans with competitive matching

• Life and income protection plans

• $500/month flexible wellness and time saver stipend

• Commuter benefits

• Annual education stipend

• Home office stipends

• Relocation support for those moving for Anthropic

• Daily meals and snacks in the office

• Have strong software engineering skills with experience building complex ML systems

• Are adept at analyzing and debugging model training processes

• Can navigate ambiguity and make progress in fast-moving research environments

• Proficiency in Python, deep learning frameworks, and distributed computing is required for this role

• Are comfortable working with large-scale distributed systems and high-performance computing

• Have experience with training, fine-tuning, or evaluating large language models

• Have a keen interest in AI safety and responsible deployment

• Can balance research exploration with engineering rigor and operational reliability

• Enjoy collaborating across research and engineering disciplines

• Experience with LLMs is a significant plus

• We require at least a Bachelor’s degree in a related field or equivalent experience