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ADAS感知算法专家_PS

BoschGroup

Wuxi, Jiangsu, China permanent

Posted: October 13, 2025

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Quick Summary

ADAS感知算法专家_PS, responsible for developing and implementing advanced sensor technologies for automotive applications, with a strong background in computer vision and machine learning.

Job Description

Bosch Powertrain Systems Co., Ltd. (RBCD), the joint venture of Robert Bosch GmbH and Weifu High Technology Group Co., Ltd., is a high tech enterprise specializing in the development, production and sales of common rail systems, exhaust gas after treatment systems, fuel cell stacks and key components. The company, based on its local R&D and project management competence, with innovative technologies, can support customers to continuously improve internal combustion engines efficiency, to reduce emission, and to accelerate the market launch of new energy products. The garget of the company is to provide the Chinese market and customers with diversified advanced powertrain products.

• Design and develop ADAS ground truth system perception algorithm, incl. multi-sensor fusion detection and segmentation algorithm, tracking algorithm, process cloud pipeline, etc.
• Design and develop innovative multi-model fusion algorithms such as map fusion modules, multi-frame local map construction modules, and road network construction modules based on static environment and dynamic objects perception results and offline maps, etc.
• Performance optimization for sensor fusion models in vehicle application.
• Cooperate with Bosch business units in China and worldwide for requirement analysis, technology transfer, and evaluate market attractiveness of new technical solutions.

Qualifications Requirement

• Master’s degree or above with major in Automotive/Automation/Computer Science/Artificial Intelligence/Electrical Engineering/Mechatronics or related.
• More than 3 years working experience in automotive electronics, experienced in ADAS, perception fusion.
• Strong knowledge in the perception domain, such as object detection, object tracking, semantic segmentation, and depth estimation based on camera/LiDAR.
• Professional English: able to use English fluently and accurately (speaking, listening, reading and writing).

Job Relevant Knowledge and Experience

• Familiarity with open-source vision libraries such as OpenCV and PCL
• Familiarity with AI-based perception backbone, frameworks, and model training
• Familiarity with filtering and optimization algorithms
• Experience in local map construction, lane detection, perception & map fusion, perception result fusion, and PnC is a strong plus
• Experience in ADAS sensors, such as cameras, LiDARs, and radars; familiarity with SD/HD map data structure is a strong plus
• Proficiency and practical experiences in ROS, Python, or C++, and developing in Linux

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