大疆卓驭感知算法工程师面试

Core Viewpoint - The article discusses the recruitment process and qualifications for a dynamic target perception algorithm engineer in the autonomous driving industry, highlighting the importance of various technical skills and experience in sensor fusion and deep learning [4][6][8]. Group 1: Job Responsibilities - The role involves processing large amounts of autonomous driving data, building automated ground truth labeling systems, and designing cutting-edge AI and vision technologies [6]. - Responsibilities include detecting static scene elements like lane lines and traffic signs, tracking dynamic targets, and predicting the future trajectories and intentions of moving objects [8]. - The engineer will work on multi-sensor fusion, depth estimation, and developing calibration methods for various sensors [8]. Group 2: Qualifications - Candidates should have a master's degree in computer science, automation, mathematics, or related fields, with experience in perception algorithms for autonomous driving or ADAS systems being a plus [6]. - Proficiency in programming languages such as C++ or Python, along with solid knowledge of algorithms and data structures, is required [8]. - Familiarity with multi-view geometry, computer vision technologies, deep learning, and filtering and optimization algorithms is essential [8]. Group 3: Community and Learning Resources - The article mentions a community of nearly 4,000 members and over 300 autonomous driving companies and research institutions, providing a comprehensive learning path for various autonomous driving technologies [9]. - Topics covered include large models, end-to-end autonomous driving, sensor calibration, and multi-sensor fusion [9].