Hybrid Senior Staff Computer Vision Engineer na Xpeng motors
Xpeng motors · Santa Clara, CA, Estados Unidos Da América · Hybrid
- Escritório em Santa Clara, CA
- Optimize large-scale multimodal models for low-latency inference and efficient memory usage across diverse hardware platforms.
- Apply state-of-the-art model compression techniques, including quantization (e.g., INT8/FP16), pruning, and knowledge distillation.
- Develop and integrate custom inference kernels targeting GPU or custom AI accelerators.
- Build profiling tools and performance models to analyze bottlenecks and guide optimization strategies.
- Contribute to real-world deployment efforts in autonomous driving systems, including on-vehicle testing and iteration.
- Track the latest research in efficient ML inference and integrate relevant techniques into production pipelines.
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Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field.
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Strong coding skills in C++ and Python with a focus on performance and scalability.
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Proficient in deploying deep learning models using TensorRT, ONNX Runtime, or TVM.
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Familiarity with CUDA programming and parallel computing principles.
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Solid understanding of model inference workflows and system-level performance tuning.
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Experience in quantization-aware training or post-training quantization.
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Effective communicator and collaborative team player.
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Hands-on experience with deploying vision-language or large multimodal models.
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Familiarity with low-precision inference (INT8/FP16), kernel fusion, and operator-level optimization.
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Experience in autonomous driving, robotics, or edge AI applications.
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Track record of open-source contributions or publications in ML/AI conferences (e.g., NeurIPS, ICML, CVPR).
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Background in system profiling, latency modeling, or compiler-level optimization.
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A fun, supportive and engaging environment
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Infrastructures and computational resources to support your work.
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Opportunity to work on cutting edge technologies with the top talents in the field.
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Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving
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Competitive compensation package
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Snacks, lunches, dinners, and fun activities