1886年，梅赛德斯-奔驰集团的两位创始人戈特利布·戴姆勒与卡尔·奔驰发明了汽车，由此开启了梅赛德斯-奔驰的历史征程。作为汽车工业的引领者，梅赛德斯-奔驰始终将安全、可持续的未来出行方式视为发展动力和己任，为此不断对创新、绿色的出行技术加大投入，以打造安全、卓越、令人向往的汽车产品。梅赛德斯-奔驰致力于持续投入并打造高效的动力系统，为全面电动的未来奠定坚实基础：在市场条件允许的情况下，三叉星徽品牌致力于实现全面纯电动的目标。从“电动为先”到“全面电动”，这家全球闻名的豪华汽车制造商正在加速奔向零排放和软件驱动的未来。此外，梅赛德斯-奔驰同样在智能互联、自动驾驶及全新出行解决方案等领域不断深耕，并不断致力于践行对社会与环境的坚定承诺。
自动标注算法工程师（应届生招聘）
Objective of job- Design and develop MB advanced auto-labelling platform, include 4D object, Landmark and BEV auto-labelling functions.
- Architecture design for ground truth training datasets release.
- Auto-labelling pipeline CICD and MLOps.
- Cross function coordinate between auto-labelling pipeline and manual labelling services.
- Define manual labelling software requirement, coordinate the labelling supplier.
- Labelling platform architecture design.
- State-of-the-art auto-labelling algorithm research and study.
- Design and develop MB advanced auto-labelling platform, include 4D object, Landmark and BEV auto-labelling functions.
- Auto-labelling pipeline CICD and MLOps
- Coordination between auto-labelling pipeline and manual labelling services, define manual labelling software requirement, coordinate the labelling supplier.
- Next generation labelling platform architecture design.
Qualification
Master’s degree or above in Computer Science/Robotics/Electronics/Automation and other related majors;
Deep understanding and hands on experience on computer vision, deep learning and robotics.
Solid research background on sensor fusion, 3D object detection, object tracking.
Hands on experience with auto-labelling system or training dataset generation.
Hands on experience with object detection, segmentation based on LiDAR.
Familiar with ROS programming and related tools usage.
Proficient in C++ and Python programming. Good code style is needed.
Hands on experiences on HD mapping automation is a plus.
Hands on experiences on BEV related algorithm development or deployment is a plus.