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Open nowPosted 644 days ago

机器人感知算法工程师

tarsrobot/index83 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now机器人感知算法工程师tarsrobot/index · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. tarsrobot/index postings stay open a median of 15 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 644 days ago

tarsrobot/index median: 15 days open

The posting

1、3D感知算法开发：负责机器人感知核心算法的开发与落地，包括3D目标检测与跟踪、Occupancy栅格构建、场景理解与重建等，支撑工业场景下的精细操作与避障需求。 2、多传感器融合与标定：负责双目、环视、深度相机及LiDAR等多类型传感器的接入与工程化适配，完成内外参标定、数据预处理滤波、运动畸变补偿等底层开发，实现多模态感知融合。 3、感知数据闭环建设：参与搭建感知数据闭环工程体系，推进自动化数据标注、感知量化评测、感知节点看护及复杂场景数据挖掘等流程的落地与迭代，支撑算法持续优化。 4、算法工程化与真机部署：将感知算法方案转化为可部署的高效工程代码，完成性能优化与工程化封装，配合运动控制与操作团队实现感知-决策-执行链路闭环。 5、前沿技术跟进：跟踪具身智能与机器人感知领域的前沿进展（如VLM/VLA中的感知模块、3DGS重建等），评估其在工业机器人场景的适用性并推动落地验证。

1、基本门槛：自动化、电子工程、计算机科学、机器人学等相关专业硕士及以上学历，3年以上智能驾驶/机器人感知算法实战落地经验。 2、工程开发能力：精通Linux系统开发环境，具备扎实的C/C++工程开发能力，能独立完成算法模块的高效编码、性能优化与工程化封装；熟悉Python用于算法原型验证。 3、专业方向经验：在以下至少一个方向有工程实践经验：传感器融合、3D目标检测与跟踪、Occupancy预测、SLAM/VIO、机器人视觉伺服、多模态感知融合。 4、深度学习基础：熟悉PyTorch/TensorFlow等主流框架，搭建过基于CNN/Transformer的感知检测分割模型，具备算法选型与落地优化能力者优先。 5、加分项：有具身智能/人形机器人/工业机器人感知落地经验者优先；有手眼标定、抓取位姿估计、灵巧操作感知相关经验者优先；在ICRA/IROS/RSS/CoRL等机器人顶会发表过相关论文者加分。 6、软性素质：具备较强的问题分析与调试能力，良好的跨团队沟通协作能力，能高效推进算法从研发到真机部署的全链路落地。

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