Sasha focused on backend and server development, contributing to both IBM/vllm and rmusser01/llama.cpp repositories. In IBM/vllm, Sasha resolved a critical illegal memory access bug that occurred with advanced features like chunked prefill and xformers, introducing regression tests and updating metadata handling to ensure model stability during complex prompt configurations. For rmusser01/llama.cpp, Sasha implemented an LCS-based server slot allocation algorithm in C++, optimizing task-slot matching and improving resource utilization. Their work demonstrated strong skills in C++, algorithm optimization, and debugging, delivering robust solutions that enhanced reliability and efficiency in machine learning model serving environments over two months.