Delivery Operations Engineer

<p>Job Description: </p><p>1. On-site autonomous vehicle operation and debugging, able to deploy and maintain projects based on the Linux environment, use the fleet management system (FMS) to control and monitor vehicle and equipment status, on-site integration testing or real ship operation problems and KPI data recording, and timely handling of abnormal situations to ensure smooth testing,</p><p></p><p>3. Lead joint R&D and engineering departments to conduct problem retrospectives, using data logging disassembly, scenario recreation, and other methods to locate the root cause of the problem, and form a clear troubleshooting logic and process record;</p><p>4. Timely synchronize the progress of on-site problem detection with the site, finally output a clear problem conclusion (such as software bugs, hardware failures, inadequate scene adaptation, etc.) and solution suggestions, and push the problem closed-loop. </p><p></p><p>6. Responsible for compiling unmanned operation and maintenance-related documents, tracking software version iterations, operation and maintenance process optimization, and timely updating related documents to ensure that documents and actual business scenarios are synchronized, and provide unified operations and reference for the R&D, operation and maintenance, and on-site teams;</p><p>7. Collaborate with simulation testing team, on-road testing team, receive unmanned driving software testing data to participate in post-test review meeting, feedback to R&D team the software optimization points found in the test, assist in formulating iteration improvement plans, and push software performance and functional quality Continuous improvement. </p><p>Requirements:</p><p>1. Bachelor's degree or above from a public university, majoring in Computer Science and Technology, Automation, Electronic Information Engineering, Vehicle Engineering (Intelligent Networking Direction), etc.;</p><p>2.3 years of relevant work experience in the unmanned driving industry, those who have L4 level unmanned driving project experience are preferred;</p><p>3. Autonomous vehicle sensor calibration (lidar, GNSS, camera, etc.) work;</p><p>4. Familiar with the architecture of unmanned driving systems (such as perception, decision, control modules), common sensors (laser radar, camera, millimeter-wave radar) installation and working principles are preferred;</p><p>5. Data processing ability: Master data cleaning and analysis basic methods, those who have experience in log analysis and scene data interpretation are preferred;</p><p>6. Tools and system application: Have Linux, Docker, Shell, etc. technology stack; understand the use of unmanned driving data management platform (such as ROS, Apollo Data Platform), simulation test tools (such as Prescan, Carsim) or fault diagnosis tools, and have basic software version management (Git) ability.</p>