Research Engineer Production Model Post-Training
AI safety and research company building reliable, interpretable, and steerable AI systems, including the Claude product family and developer platform.
Maintainer signals as of 9/24/2026
Funding history
About Anthropic
Anthropic PBC develops frontier AI systems and deploys them through Claude products and the Claude Platform, with a stated focus on safety, interpretability, and steerability.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will implement, scale, and improve post-training techniques for frontier models. You will build fine-tuning and evaluation pipelines, develop model-performance tools, debug training and model-behavior issues, and translate research methods into reliable production implementations.
Requirements
- Software engineering
- Machine learning system development
- Distributed system
- High-performance computing
- Large language model training, fine-tuning, or evaluation
- Python
- Deep learning framework
- Distributed computing
Responsibilities
- Implement and optimize post-training techniques at scale on frontier models
- Conduct research to develop and optimize post-training recipes
- Design, build, and run pipelines for model fine-tuning and evaluation
- Develop tools to measure and improve model performance
- Translate emerging research techniques into production-ready implementations
- Debug issues in training pipelines and model behavior
- Establish best practices for reliable, reproducible model post-training
Benefits
- Visa sponsorship
- Equity donation matching
- Vacation leave
- Parental leave
- Flexible working hours
