Posted 12 Jun 2026 (147 days ago) · Job 55972 · Read from the employer's SmartRecruiters board, last checked 6 Nov 2026, 11:03 UTC

智驾系统架构师_XC

Bosch · Shanghai, Shanghai, China

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Full time

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Company Description

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

 

Job Description

1、系统架构设计:城市无图E2E平台的算法系统架构开发,主导设计从传感器原始数据输入到车辆控制指令输出的全链路软件架构,定义清晰的模块边界,模块功能和任务、算法模块间接口协议和数据流。UML文档化设计变更的评审结果。
2、算法方案评审: 评审感知、建图,预测、规划等核心算法的技术方案,评估工程可行性以及与现有架构的兼容性,提出算法模块的改进建议。 
3、功能评测建立:建立评估系统功能性能的多分类场景集,根据模块功能链路架构,评估不同发版之间的性能提升和回退,对模块提出量化的修改要求和架构变更需求。
4、跨团队合作: 强有力的推动和协调能力,能够与TPM,各模块开发团队(感知、预测、规划、控制、底层系统)及测试团队紧密合作,统一技术认知,确保架构方案的成功实施。

Qualifications

1、电子信息, 车辆工程,计算机、软件工程等本科以上学历等; 
2、编程语言: 精通C++,3年以上嵌入式复杂系统开发经验,熟悉ROS/ROS2框架,熟练使用linux开发系统。 
3、至少完整参与过一个城市无图NOA项目的工程化落地,并在其中主导模块算法架构设计。 
4、工具链: 精通Docker、Git。仿真平台(如CARLA、LGSVL),数据平台、模型训练框架(如PyTorch、TensorFlow)等。 
5、至少主导过一下任意一个模块的开发过程: 
1)熟悉深度学习模型(如CNN、RNN、Transformer)在计算机视觉中的应用,包括目标检测(如YOLO、Faster R-CNN、DETR)、语义分割(如SegNet、DeepLab)、实例分割、车道线检测、可行驶区域分割等。 
2)熟悉BEV(Bird's Eye View)感知技术,如BEVFormer、LSS(Lift, Splat, Shoot)等,以及时序融合技术。 
3)熟悉环境建模技术,包括栅格图(Grid Map)、占据网络(Occupancy Network)、动态场景图(Scene Graph)等。 
4)熟悉常见的运动规划算法,如A、D、RRT*、Lattice Planner、EM Planner等,以及基于优化(如MPC)的规划方法。 
5)熟悉强化学习(RL)或模仿学习(IL)在二阶段规划中的应用,以及端到端规划工程应用的问题和前沿进展。 

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