Worked on the volcengine/verl repository to enhance the reliability of data preprocessing pipelines used in machine learning workflows. Addressed a bug in Python code where tensors in preprocess_packed_seqs were not properly padded to the required alignment size, which could lead to index errors during model training and inference. The solution involved padding shorter tensors with zeros, ensuring consistent tensor lengths and preventing out-of-range indexing. This change improved the robustness and stability of the data preprocessing path, aligning behavior across related modules. The work demonstrated attention to maintainable code practices, including clear documentation and adherence to contribution guidelines for production environments.