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Open nowPosted 67 days ago

校招-GPGPU芯片架构师

nio/campus869 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now校招-GPGPU芯片架构师nio/campus · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% 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. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 67 days ago

nio/campus median: 1 days open

The posting

1.持续跟踪全球 AI 芯片行业动态，国内外AI 芯片厂商的技术路线与产品发布。 2.深入分析竞品的架构微架构设计、性能指标、生态布局，调研 AI 推理市场的需求趋势、典型应用场景与客户痛点，输出竞争分析报告为芯片架构定义提供输入。 3.跟踪AI芯片、云端推理服务、大模型推理加速等领域的前沿技术,提前布局技术方向。 4.深入理解大模型的部署，并行策略等，优化模型在多芯片/多核间的映射与通信效率 5.针对Transformer等主流AI大模型，参与 GPGPU芯片的架构定义与设计，涵盖指令集的定义、计算单元、访存系统、数据通路、多片系统结构、任务调度等 6.与算法团队紧密合作,分析AI模型的计算模式与瓶颈,提出硬件架构的定制化解决方案 7.关注芯片 PPA（Performance, Power, Area）指标，参与架构层面的权衡与优化 8.与硬件设计团队协作，理解 RTL 设计与验证流程，推动架构方案到实现的落地 9.深入理解 NVIDIA CUDA 生态，包括 GPGPU 编程模型、NCCL 通信库、cuDNN/cuBLAS 算子库等，配合编译器团队优化算子实现 10.工作地点：上海/深圳/合肥

1.电子、通信、计算机等相关专业应届博士 2.扎实的计算机体系结构基础，理解处理器微架构、存储层级、并行计算等核心概念 3.熟悉 GPGPU ，SIMT架构与 CUDA 编程模型，理解 GPGPU 的工作原理 4.了解 NCCL 等 GPU 通信库的设计原理与使用方式 5.对芯片设计流程有基本认知，了解 PPA 的基本概念与权衡方法 6.具备较强的系统性思维，能够从全栈角度分析和解决问题 7.优秀的文献调研与技术分析和新技术的快速自我学习能力 8.良好的沟通协作能力，良好清晰的表达能力，良好的自顶向下的梳理能力

加分项： 1.在计算机体系结构、AI 系统、并行计算等相关方向的核心期刊或顶级会议（如 ISCA、MICRO、HPCA、ASPLOS、SC、ACL 等）发表过论文 2.在某一垂直领域（如 AI 编译器、并行计算、高性能通信、芯片架构等）有深入研究，形成系统性成果，或者在某个领域有优秀的实际项目经验或深度实践 3.有 AI 芯片公司或大厂 AI 系统团队的实习/研究经历 4.熟悉分布式训练或推理系统的实际部署与优化经验 5.经历过需求分析到芯片回片到模型部署性能调优的端到端的芯片流片经历

我们提供： 1.从市场洞察到芯片架构的全栈培养路径，由资深架构师一对一指导 2.参与下一代 AI 芯片从架构定义到流片的全流程机会 3.深度参与 AI 芯片前沿技术研究的平台与资源

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