1. Core work: Research and development of algorithms related to object segmentation and detection in autonomous driving scenarios, including semantic segmentation, panoramic segmentation, object detection, multi-source sensor joint perception (detection, segmentation, cross camera correlation), object tracking, etc;
2. Algorithm implementation: Responsible for organizing, analyzing, and mining data related to target detection, and improving the generalization of the model;
Responsible for the development, optimization, integration and debugging of target detection models/post-processing algorithms, and promoting the implementation of algorithms in actual products.
3. Frontier tracking: tracking and testing of new algorithms for deep learning object detection and recognition;
4. R&D Documents: Responsible for designing and writing relevant documents during the development process of deep learning algorithm module software.

1. Education requirements: Master's degree or above
2. Professional requirements: Computer, Communication, Mathematics, Statistics and other related majors. 3. Work experience: 3 years or more of relevant work experience
4. Professional knowledge: Proficient in using C++/C or Python; Familiar with at least one deep learning open source framework, such as Python, TensorFlow, etc; Familiar with common 2D/3D object detection algorithms, experience in autonomous driving or published papers in related fields is preferred; Having a good technical background in image processing, machine learning, computer vision, and other fields; Understand model pruning, transplantation, and other tasks
5. Ability and quality: Proficient in reading English literature and implementing relevant algorithms based on the literature; Possess good learning ability, passion for technical expertise in the professional field, courage to challenge, and good at analyzing and solving problems; Strong sense of responsibility and good teamwork spirit.