小米
端到端算法工程师实习生
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职位描述
1. Develop quantization, sparsity, pruning, and distillation techniques to enhance the production-level autonomous driving models. 2. Optimize, convert, and deploy autonomous driving models (e.g., ONNX models) that operate efficiently on diverse hardware (GPU, CPU, in-house AI ASIC). 3. Design and implement custom kernels using C++ and CUDA to accelerate model operations and pre/post-processing pipelines. 4. Perform a systematic benchmarking, scaling, and validation of inference performance acro
任职要求
1. Familiar with techniques like quantization, sparsity, pruning, and distillation for edge and real-time inference. 2. Strong proficiency in Python and C++, and deep learning frameworks such as PyTorch. 3. Hands-on expertise with CUDA programming, low-level performance profiling, and compiler-level optimization. 4. Strong understanding of computer systems and architecture, with experience deploying AI models on GPUs and NPUs. 5. Experience with model optimization tools like ModelOpt/ONNXSim/Ten