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 a keen interest in AI safety and responsible deployment,
Experience with LLMs is a significant plus,
Proficiency in Python, deep learning frameworks, and distributed computing is required for this role,
We require at least a Bachelor's degree in a related field or equivalent experience

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

Research Engineer (Production Model Post Training)

Job Type