Worked on the huggingface/trl repository to address a critical issue in the GRPO trainer, focusing on correct application of reward scaling during reinforcement learning model training. The solution involved mapping the scale_rewards configuration from boolean to string options and updating the advantage calculation logic to ensure rewards were scaled as intended. This fix restored the expected training stability and reproducibility across experiments. The work demonstrated strong debugging skills in machine learning training loops, effective use of configuration management, and proficiency in Python and Git workflows. All changes were traceable through linked commits and pull requests, supporting transparent code review processes.