Worked on the kvcache-ai/sglang repository to address a critical memory-management issue in the DeepSeek weight loading process. Using Python and leveraging data processing and machine learning expertise, implemented a solution that defers the materialization of the weights dictionary when quantization is not required. This approach reduced peak memory usage and prevented out-of-memory errors during weight loading, particularly benefiting large model deployments in production environments. The fix maintained consistent behavior across quantized and non-quantized paths, ensuring stability. The work focused on improving reliability and efficiency in model loading workflows, demonstrating attention to both performance optimization and robust engineering practices.