Research Engineer, Production Model Post-Training

About Anthropic

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

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

You may be a good fit if you

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

Fähigkeiten

PythonML / AI

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