Worked on stabilizing the image processing workflow in the pytorch/ao repository, focusing on backend development and asynchronous programming using Python. Addressed a memory leak in the image processing endpoint by ensuring figures were properly closed after use, which reduced peak memory usage during image generation and improved reliability under higher load. The technical approach emphasized robust memory management and reinforced resource cleanup patterns, enhancing maintainability and predictability of the pipeline. No new features were released during this period, as the primary contribution centered on improving the stability and operational risk profile of the media processing infrastructure through targeted bug fixes.