Worked on stability and reliability improvements for distributed systems in the huggingface/trl and linkedin/Liger-Kernel repositories. Addressed distributed training robustness by ensuring the vLLM client initializes only on the main process when operating in server mode, preventing failures during distributed initialization. In linkedin/Liger-Kernel, restored missing low-level API imports to align actual functionality with documented features, ensuring API endpoints worked as described. Focused on backend development and code refactoring using Python, with an emphasis on API integration and distributed systems. The work prioritized maintainability and robustness, reducing edge-case failures and supporting consistent behavior across complex machine learning environments.