About the job
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.
Responsibilities
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
Qualifications
Minimum
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
Preferred
Have experience with LLMs
Have a keen interest in AI safety and responsible deployment