数据闭环算法工程师_XC
Bosch · Shanghai, Shanghai, China
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公司描述
职位描述
数据闭环体系搭建与落地：负责自动驾驶算法业务全链路数据闭环体系设计与搭建，日均处理亿级传感器原始数据及标注数据，保障数据从采集、处理到模型训练、评测的端到端流转，支撑感知、决策规划等端到端模型的高效训练和数据采样
数据闭环工具链研发：①云端数据处理pipeline开发：针对标注数据、场景数据，设计并落地数据清洗 （去噪、去重、异常过滤)、解析、切片、抽帧、送标 （对接标注平台）的全流程自动化pipeline；②优化pipeline吞吐量与延迟，目标支撑日均10万+场景数据处理，服务算法团队数据生产需求；③推动工具链部署落地，解决线上运行故障 （如数据阻塞、接口兼容问题)，保障工具链可用性。
高价值场景数据挖掘体系建设：①搭建“规则+大模型”双驱动的数据挖掘产线：针对规则挖掘，设计接入多种传感器、定位、感知、底盘、车身信号并优化规则策略；针对大模型挖掘任务，完成数据方案制定、模型微调、loss优化、模型评测等；②与算法团队协作迭代挖掘策略，提升 corner case 召回率。
职位要求
本科及以上学历，计算机、软件工程、自动化、电子信息等理工科专业：
2年及以上自动驾驶数据体系相关经验，有大厂/独角兽企业数据工厂搭建、量产项目经验者优先；
精通Python、C++，熟悉Linux操作系统 （常用指令、Shell脚本)，具备良好编程习惯（代码注释、Git版本管理、CI/CD流程）；
掌握常见主流传感器数据处理：LiDAR （点云去噪/拼接/动静态补偿）、Camera （畸变校正/图像融合)等，精通H264/H265/YUV/MJPEG等编解码方式，有定制数据格式经验（如自定义传感器数据封装格式、私有标注格式)者加分；
熟悉自动驾驶中间件：ROS2（节点通信、Msq/Srv定义、参数服务器配置)、DDS(QoS策略优化）；
具备强问题解决能力，能快速定位数据处理、工具链运行中的技术故障：
其他信息
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