XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. We are seeking an algorithm engineer with strong system-design skills to develop state-of-the-art computer vision and machine learning algorithms for UMF Lane Fusion in autonomous driving systems. In this role, you will fuse lane lines, road boundaries, and other static road elements across perception sources and time to generate accurate, stable, and semantically rich road representations. The Lane Fusion system must operate with low latency and high availability on a real-time, safety-critical vehicle platform. You will work with cross functional research and development teams in a rapidly paced environment. Your work will ensure that we deliver the most reliable mass market autonomous driving solution.
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Job Type
Full-time
Career Level
Senior