LLM Optimization Engineer

Responsibilities
Design and implement efficient parallel computing strategies and memory management mechanisms to improve end-to-end throughput and latency Develop and optimize high-performance training and inference frameworks, maximizing hardware compute and memory bandwidth utilization Qualifications
Proficiency in Python and C++, with strong foundations in data structures, algorithms, and systems programming Solid experience with PyTorch, including a deep understanding of model execution workflows, operator invocation, and computation graph mechanisms Familiarity with high-performance computing (HPC) concepts such as parallel computing, memory hierarchy, and operator fusion Basic understanding of accelerator architectures (e.g., GPU, NPU), including compute units, memory systems, and communication mechanisms Preferred Qualifications
Experience with mainstream LLM inference acceleration frameworks such as vLLM and SGLang, with hands-on performance optimization experience Fa...