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Open nowPosted 15 days ago

AI编译器专家（存算与AI） - 芯片研发

ByteDance19,209 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowAI编译器专家（存算与AI） - 芯片研发ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 15 days ago

ByteDance median: 2 days open

The posting

团队介绍：聚焦存算一体芯片设计，主要围绕AI大模型应用场景进行高能效计算技术创新，设计多款基于存算一体架构的高能效AI芯片，突破传统冯・诺依曼架构下的 "内存墙" 瓶颈，提升能效比、降低算力成本。团队具备独立流片与量产落地能力，累计申请专利近300项，核心专利覆盖“底层器件-核心架构-工程落地”全流程。同时与字节各团队算力需求整体协同，更好的发挥存算一体芯片的技术价值，共同为AI业务提供高能效算力底座。

1、面向自研NPU和存算一体架构，负责AI编译器的设计、开发与优化，覆盖模型导入、计算图优化、中间表示转换、后端代码生成和运行时对接； 2、对接PyTorch、ONNX等模型生态及上层计算框架，支持CNN、Transformer和大语言模型的图编译、运行与性能调优； 3、负责面向目标硬件的编译映射与调度，包括Tiling、并行映射、调度、片上内存规划、DMA编排等，设计和优化内存规划算法，结合Tensor生命周期、片上SRAM容量、外部存储带宽等，优化内存复用和数据驻留，削减数据搬运开销； 4、协同算子、Runtime和硬件团队优化计算效率、内存占用、数据搬运、执行延迟及吞吐率； 5、从可编程性、编译映射、硬件利用率等角度参与软硬件协同设计，为指令集、存储层次、同步机制以及NPU微架构提供软件侧需求和评估； 6、建设编译器测试与回归体系，覆盖编译正确性、数值精度、模型兼容性、性能稳定性及异常场景，参与精度调试工具、性能分析工具和编译器自动化测试体系建设。

1、计算机、电子工程、自动化、微电子或相关专业，硕士学位及以上，具有3年以上AI编译器、传统编译器、深度学习框架或异构计算相关研发经验； 2、理解编译器基本原理，熟悉中间表示、控制流与数据流分析、模式匹配、指令选择、寄存器分配、代码生成等；熟悉至少一种编译器基础设施或AI编译系统，如MLIR、LLVM、TVM、XLA、IREE、Glow或自研编译器； 3、熟悉深度学习计算图和常见算子，理解卷积、矩阵乘、归一化、Attention等计算原理、数据布局和性能特征； 4、理解CPU、GPU、DSP、NPU等异构计算架构，熟悉缓存、片上存储、DMA、SIMD/SIMT、流水线及并行计算的基本原理； 5、具备性能分析能力，能够根据Profiling数据定位计算、访存、同步、数据搬运和调度瓶颈； 6、具备良好的沟通能力，能够与芯片架构、算子、Runtime、框架和模型团队紧密协作。

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