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Open nowPosted 66 days ago

低精度量化/模型压缩算法工程师

agirobot/referral515 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now低精度量化/模型压缩算法工程师agirobot/referral · Shanghai, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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

  4. CV RocketApplied on agirobot/referral's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

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. agirobot/referral postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 66 days ago

agirobot/referral median: 1 days open

The posting

1、负责具身智能模型、机器人多模态感知/决策模型的轻量化压缩与低精度量化优化，落地端侧/边缘部署，在保精度前提下降低推理时延、显存占用与设备功耗。 2、主导量化体系迭代，包含FP8/INT8/FP4/INT4混合精度量化、PTQ/QAT量化训练，解决具身模型动态输入、时序特征、控制任务带来的量化误差、漂移、精度掉点问题。 3、开展模型蒸馏、结构化/非结构化剪枝、稀疏化、算子融合、推理图优化等压缩方案，针对机器人实时交互、导航、操控场景做专项性能迭代。 4、对接推理框架与硬件平台，完成模型转换、算子适配、内存与调度优化，打通训练压缩—量化校准—端侧部署全链路，输出标准化压缩量化工具与基线。

1、硕士及以上学历，计算机、人工智能、自动化、电子信息等相关专业，3~5年模型量化、模型压缩、端侧AI优化经验，有具身智能/机器人模型优化经验优先。 2、精通各类低精度量化算法，熟练掌握PTQ、QAT、混合精度量化方案，熟悉剪枝、蒸馏、稀疏化等主流模型压缩方法，具备精度修复与误差调优能力。 3、熟练使用PyTorch/TensorRT/ONNX，熟悉NPU/RKNN等端侧推理部署流程，具备算子优化、推理加速、显存功耗优化实战经验。 4、熟悉多模态、时序感知、机器人决策控制类模型特性，能独立完成模型压缩量化方案设计、实验验证、指标复盘与工程落地。

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