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Open nowPosted 32 days ago

校招-AI模型部署与性能优化工程师

nio/campus870 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now校招-AI模型部署与性能优化工程师nio/campus · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 32 days ago

The posting

1. 负责将客户常见智能辅助驾驶算法模型（CNN，Transformer，LLM/VLM/VLA模型）部署到公司大算力芯片平台，解决部署过程中涉及的算子不支持、精度不正确, 规格不匹配等问题。 2. 运用性能分析工具对模型进行全栈性能剖析，识别计算、内存、调度瓶颈，通过图融合、算子替换、内存优化以及其他软硬件优化技术，提升推理速度和吞吐量。 3. 配合客户实施PTQ量化方案，定位并解决量化或其他过程引入的精度损失问题。 4. 系统性地诊断并解决单模型部署和多模型并发场景下的稳定性问题。深入定位Core Dump / Crash的根本原因（内存越界、资源竞争等）并推动解决。 5. 理解客户需求，提供部署、性能调优方案和建议。建设并维护车载/机器人场景 Model Zoo，输出最佳实践案例文档，降低客户使用门槛。

1. 硕士以上学历，有智能辅助驾驶/机器人算力平台AI部署项目经验者优先。 2. 精通Python和C++编程，熟悉PyTorch、TensorFlow、ONNX等深度学习框架中的一种或多种。 3. 熟悉TensorRT、TVM、ONNX Runtime、vLLM、llama.cpp等主流推理引擎/框架中的一种或多种。 4. 熟悉常见网络模型结构和算子，具备模型部署、算子开发和调优经验。掌握系统级别和算子级别 Debug & Profiling 实战技能，熟悉Nsight Systems、perf、Vtune等性能分析工具。 5. 熟悉GPGPU或NPU等AI加速芯片硬件特性、了解AI软件栈，有软硬协同经验者优先。 6. 积极主动，勇于承担， 具备良好的团队合作精神、沟通协调能力和技术推动力。

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