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Open nowPosted 64 days ago

校招-AI芯片加速算法工程师

nio/campus867 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now校招-AI芯片加速算法工程师nio/campus · Shanghai, Chinese Mainland

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on nio/campus's own form.

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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. nio/campus postings stay open a median of 1 days.

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 64 days ago

nio/campus median: 1 days open

The posting

1.结合自研芯片硬件架构特性，开展软硬件协同算法研究，参与芯片需求定义，参与算法、硬件、软件联合优化，解决精度、时延、吞吐、显存占用等核心瓶颈。 2.参与工作包括但不限于：模型量化、KV cache压缩、算子加速、高性能 Kernel 开发、图优化、显存调度等，充分释放芯片硬件算力、提高能效。 3.参与深度学习引擎适配，完成主流模型移植、性能建模、精度调优，搭建性能分析、自动化测试验证工具，定位并解决性能退化、精度异常问题。 4.跟踪异构计算、AI 编译器、算子优化、量化压缩等前沿技术，完成原型验证、技术方案输出，推动技术落地产品版本，支撑具身智能、Agent 平台等业务落地。

1.学历专业：2027 届硕士 / 博士，计算机体系结构、计算机软件、人工智能、通信与网络、电子与信息、微电子、自动化、应用数学等相关专业； 2.编程基础：熟悉 C/C++ 、Python；熟悉 Linux 开发环境，掌握性能分析工具，具备良好调试、性能调优能力。 3.知识储备：熟悉计算机体系结构、存储层次、NPU/GPU计算基本原理；了解深度学习基本原理，熟悉 PyTorch/vLLM/SGLang等至少一种框架或引擎。 4.具备较强算法思维，能够分析性能瓶颈，独立完成技术原型实现，具备良好文档、方案撰写能力。自我驱动，热爱底层技术，善于定位复杂系统问题，具备良好沟通与团队协作。 优先（满足其一即加分） 有 CUDA/OpenCL/ 异构 NPU 开发、GPU算子库开发优化经历； 有 AI推理引擎、量化算法、稀疏计算、芯片架构设计相关项目经验； 硕士 / 博士课题涉及神经网络加速、芯片软硬件协同、高性能计算； 有开源框架开发、模型部署优化实战经历，或有相关顶会论文经验。

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