United States
Lead the engineering team to develop GPU-accelerated computing. Responsible for project execution, resource planning, and cross-departmental collaboration to deliver scalable, high-performance solutions. Develop technology strategies, mentor engineers, and ensure the innovation and quality of CUDA-based AI, scientific computing, and data-intensive application systems.
Developed and optimized CUDA based frameworks, enhancing GPU performance for high performance computing and AI applications.
Responsible for software development and performance optimization of the CUDA parallel computing platform, participating in the design and debugging of GPU-accelerated algorithms to enhance the execution efficiency of high-performance computing and data processing systems.
Design a highly available backend architecture to ensure stable operation of parallel tasks across hundreds of servers.