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Open nowPosted 231 days ago

具身模型训练推理框架工程师实习生

anker-in/campushirecn495 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now具身模型训练推理框架工程师实习生anker-in/campushirecn · 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. anker-in/campushirecn 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 231 days ago

anker-in/campushirecn median: 1 days open

The posting

安克实习生项目是面向正式校招岗位的人才培养与选拔通道。实习期间将按照校招标准进行系统的培养与综合评估,表现优秀者可直接获得校招转正机会,提前锁定正式校招席位。我们以严肃、长期的视角对待每一位实习生,也期待与你共同成长。

【你将参与】 1.负责端侧（Edge / On-device）深度学习模型的部署与工程化落地，覆盖训练、转换、推理到实际设备运行的完整流程 2.参与端侧模型的推理性能优化，包括但不限于： (1).模型量化（PTQ / QAT） (2).模型压缩（剪枝、蒸馏、结构优化等） (3).推理加速与内存优化 3.基于主流端侧推理与训练框架开展开发与优化工作，如 TensorRT / QNN / TFLite / MNN / PyTorch 等 4.参与或协助训练框架与部署工具链的开发与维护，包括模型转换、算子适配、性能分析与问题定位 5.跟进端侧 AI、模型压缩与部署方向的前沿技术，参与团队内部技术讨论与方案设计

1.研究生及以上学历（在读），计算机、人工智能、电子工程、自动化等相关专业，可长期实习（3 个月及以上） 2.具备扎实的深度学习基础，熟悉主流模型结构，如 CNN / Transformer / 主流视觉或多模态模型 3.熟练使用 C / C++ / Python 中至少两种语言，具备良好的工程代码能力 4.使用过至少一种主流深度学习或推理框架： PyTorch / TensorRT / QNN / TFLite / MNN 等 5.了解或具备以下任一方向经验者优先： (1). 模型量化（PTQ、QAT） (2). 模型压缩（剪枝、蒸馏、低比特、结构优化等） (3). 端侧推理优化、算子性能分析 6.熟悉 Linux 开发环境，具备端侧设备（如 ARM / NPU / DSP 等）调试或部署经验者优先 7.具备良好的学习能力、问题分析能力与团队协作意识，对底层原理和工程优化有持续兴趣

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