Job Description 1.GPU/NPU Software Development and Optimization Implement high performance kernels, operators, and libraries for GPU/NPU. Profile with Nsight Systems/Compute, VTune, Perf, TensorBoard, etc., identify bottlenecks and apply code level optimizations. 2.Robotics AI System Prototyping, Development and Tuning Collaborate with Algorithm and Hardware teams to deploy various models on development platforms (GPU/NPU-based) with real time performance constraints. Build automated benchmarks, generate performance reports, and propose optimization strategies. 3.Agentic System Research (KV-Cache etc.) Design, implement, and accelerate KV Cache etc. for large model inference. Explore and prototype Agentic (agent based, self adapting) inference frameworks evaluate them in robotic AI scenarios. Qualifications * Currently enrolled in a Master's or Ph.D. program (Computer Science, Electrical Engineering, AI, Mathematics, or related fields). * Proficient in C/C++ and Python; ability to write clean, maintainable code. * Solid understanding of the CUDA programming model; 1year of hands on CUDA experience (kernel development, streams, memory management, optimization). * Experience with profiling tools such as Nsight, VTune, Perf, TensorBoard, etc. * Familiarity with Transformers, CNNs, RNNs and the typical performance bottlenecks during inference. * Good reading/writing skills in English; effective teamwork across multidisciplinary groups. * Strong passion for pushing extreme boundaries of GPU/NPU acceleration, robotics AI, and Agentic systems. Skills as Plus: * Experience with KV Cache, attention mechanism optimization, or model compression (quantization, pruning, distillation). * Hands on work with Agentic/agent based AI frameworks (e.g., ReAct, Tool Use, Auto GPT). * Development experience on NPUs or other heterogeneous accelerators. * Contributions to open source projects such as TensorRT, ONNX Runtime, OneAPI, etc. * Linux system tuning, driver development, or low level hardware interface knowledge.