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Open nowPosted 227 days ago

模型优化工程师

tranxmart/5110788 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now模型优化工程师tranxmart/511078 · Beijing, 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.

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 227 days ago

The posting

我们正在招募一名模型优化方向的应届生，参与感知/定位/预测/规划等核心模型的训练与推理全链路性能优化工作。你将在导师指导下，学习从算子层到系统层的性能分析与优化方法，深入理解深度学习模型的高效部署。 主要职责 - 参与模型在训练与推理阶段的性能分析，学习瓶颈定位方法（显存/算力/带宽/IO） - 协助实施量化/剪枝/蒸馏等模型压缩策略，理解精度与性能的权衡 - 参与基于 TensorRT/ONNX Runtime 等工具的推理加速与算子优化 - 协助构建自动化基准测试与性能回归体系 - 编写高质量工程代码与实验文档，参与性能数据分析与汇报

- 本科或硕士应届毕业生，计算机/电子/自动化/数学等相关专业 - 扎实的深度学习基础，熟悉 Transformer/CNN 等主流模型架构 - 熟练使用 PyTorch 或 TensorFlow，有模型训练与调试经验 - 了解模型推理部署的基本流程（ONNX 导出、推理引擎使用等） - 了解混合精度训练（FP16/BF16）的基本概念 - 具备 Python 编程能力，了解 C/C++ 者优先 - 学习能力强，对性能优化与系统底层有浓厚兴趣 加分项 - 有 TensorRT、TVM、ONNX Runtime 等推理引擎使用经验 - 了解 CUDA 编程基础与 GPU 架构基本概念 - 有使用 Nsight、nvprof、torch.profiler 等性能分析工具的经验 - 有量化/剪枝/蒸馏等模型压缩的实践经验（课程项目或论文均可） - 有相关竞赛（如 MLPerf、模型推理优化赛等）参赛经历 - 有高质量的学术论文或开源贡献

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