Caterpillar
From Caterpillar's careers page
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Technology, Digital and Data
Your Work Shapes the World at Caterpillar Inc.
When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
感知算法工程师（激光雷达检测）
岗位职责
负责激光雷达 3D 目标检测模型的开发与维护，覆盖矿卡、轻型车、工程设备、人员及路面障碍物等目标。
负责点云聚类、地面分割、语义分割及可行驶区域检测等算法开发，处理非结构化道路与不规则障碍物。
负责多任务感知模型（检测、分割、Occupancy 等）的设计与部署，提升车端算力利用效率。
针对扬尘、雨雾、颠簸、强光等矿山环境，优化模型鲁棒性，降低误检与漏检。
支持大规模道路测试中的问题分析、数据回流与模型持续迭代优化。
负责感知模型在车端平台（如 NVIDIA Orin）的量化、TensorRT 加速与部署，满足实时性要求。
任职要求-基本要求
计算机、自动化、电子、机器人、车辆工程、数学等相关专业本科及以上学历。
3 年以上自动驾驶感知或点云算法开发经验。
熟练掌握 C++ 和 Python，熟悉 Linux 及 ROS/ROS2。
熟悉 PyTorch 等深度学习框架，具备扎实的计算机视觉与深度学习基础。
点云检测与分割方向
熟悉主流 3D 检测模型，如 PointPillars、SECOND、CenterPoint、PV-RCNN 等，具备实际落地经验。
熟悉点云语义分割、实例分割及 Occupancy 等方法，了解 RangeNet++、Cylinder3D 等模型。
熟悉传统点云处理方法，如地面分割、欧式聚类、DBSCAN、体素滤波等。
工程部署方向
具备模型量化、剪枝、TensorRT/CUDA 加速及车端部署经验。
熟悉 PCL、Open3D、OpenPCDet、MMDetection3D 等点云与感知工具库。
具备大规模测试数据分析与问题定位能力。
加分项
矿山、港口、园区等封闭场景自动驾驶经验。
激光雷达与相机、毫米波雷达多传感器融合感知经验。
恶劣天气（扬尘、雨雾）点云去噪或感知鲁棒性优化经验。
自动标注、主动学习或数据引擎建设经验。
BEV 感知、Occupancy 网络或端到端感知方向研究与应用经验。
October 27, 2026 - November 19, 2026
Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply
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