英伟达自动驾驶算法工程师面试

Core Insights - The article discusses the competitive landscape of the autonomous driving industry, highlighting the detailed job roles and recruitment processes at companies like NV [3][4][5][6][11][12][14]. Recruitment Process - NV has a highly structured recruitment process with multiple interview rounds, including technical assessments and coding challenges [3][4][5][6][11][12]. - Candidates are evaluated on their project experiences, particularly in areas like Model Predictive Control (MPC) and Simultaneous Localization and Mapping (SLAM) [5][8][11][12]. Technical Skills - The interviews focus on advanced technical skills, including knowledge of optimization algorithms, dynamic programming, and deep learning applications in autonomous driving [5][8][11][12]. - Coding challenges often involve data structures and algorithms, such as merging linked lists and dynamic programming problems related to grid navigation [6][8][11][12]. Industry Trends - There is a noticeable trend towards standardization in the autonomous driving technology stack, with a shift from numerous specialized roles to more unified models [22][25]. - The article emphasizes the importance of community and collaboration among professionals in the autonomous driving sector to navigate the evolving landscape [22][25]. Community and Networking - The establishment of a community platform for professionals in autonomous driving is highlighted, aiming to facilitate knowledge sharing and job opportunities [19][22][25]. - The community includes members from various companies and research institutions, fostering collaboration and support for job seekers [19][22][25].