About this role
About the Role Anthropic’s production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you’ll train our base models through the complete post-training stack to deliver the production 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. This role may require responding to incidents on short-notice, including on weekends.
What You'll Do
- 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
What We're Looking For
- Thrive in controlled chaos and are energised, 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
- Strong candidates may also: Have experience with LLMs; Have a keen interest in AI safety and responsible deployment
- We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.
Nice to Have
- Experience with LLMs
- Interest in AI safety and responsible deployment
Compensation & Benefits
- Annual Salary: $350,000 - $500,000 USD
- Visa sponsorship available for some roles; Anthropic supports visas where possible.