Core Viewpoint - Didi has a strong technical foundation in the autonomous driving sector, particularly in perception algorithms, and is a key player for those interested in pursuing careers in this field [2]. Group 1: Interview Process - The interview process for the perception algorithm position at Didi consists of three technical rounds, with a focus on project details and technical principles [2]. - Candidates are advised to thoroughly understand every detail on their resumes, as interviewers may ask in-depth questions [2]. Group 2: Technical Questions - The first round includes self-introduction and targeted questions about the candidate's research output and direction [3]. - Candidates are asked to explain the core innovations of their papers, leading to discussions on 2D object detection [4]. - The evolution of 2D object detection algorithms from traditional methods to deep learning is a key topic [5]. - Understanding of Anchor-Free detection, specifically the core process of the FCOS algorithm, is assessed [6]. - Candidates are questioned about their familiarity with end-to-end detection algorithms, reflecting the latest developments in the field [7]. - The mechanism of DETR in achieving end-to-end object detection is explored in depth [8]. Group 3: Project Experience - Candidates are expected to present their project experiences, such as a perception project based on the BEVDet model, detailing the algorithm architecture and detection process [9]. - Interviewers inquire about specific challenges faced during the implementation of algorithms in real-world applications and the solutions devised [10]. Group 4: Coding Assessment - A coding challenge is included, where candidates must write the NMS (Non-Maximum Suppression) post-processing code on-site [11]. Group 5: Community and Networking - A community has been established for job seekers in autonomous driving and related fields, with nearly 1,000 members from various companies, providing a platform for networking and support [12].