AD Data Toolchain Engineer ID217123

该职位来源于猎聘 China is Mercedes-Benz’s largest passenger car market globally. At Mercedes-Benz R&D China, we are committed to delivering China-fit ADAS/AD solutions through cutting-edge technologies for our Chinese customers. We are now seeking talented professionals who share our passion and dedication to building advanced, China-oriented ADAS/AD systems. Responsible for the development, maintenance, and operational support of the autonomous driving data closed-loop toolchain, covering core data pipeline services, toolchain platform consolidation, and multi-cloud deployment operations — with a focus on cloud-based full-stack engineering to support the entire data lifecycle for autonomous driving development and operations. Key Responsibilities Data Toolchain Development & Maintenance: Own the development, operations, and continuous optimization of the autonomous driving data toolchain, responding swiftly to evolving business requirements. Core service areas include:

• Data Lifecycle Management Services: Maintain end-to-end pipeline data assets and provide standardized APIs covering bag management, joined-bag processing, geometric data management, ground-truth data management, project management, tagging, and topic management
• Data Selection & Annotation Platform: Operate and optimize the data annotation and fine-selection platform, enabling annotators to efficiently curate high-quality datasets for downstream consumption; maintain and iterate on the internal MB ground-truth annotation platform Cloud Deployment and Operations
• Manage service deployment, day-to-day operations, monitoring, troubleshooting, and issue resolution across multi-cloud environments (public cloud, compliance cloud, etc.)
• Establish and maintain alerting and incident response workflows to ensure service availability and compliance Requirements Management & Coordination
• Interface with business stakeholders to clarify requirements, align on solutions, and manage task breakdown, scheduling, and end-to-end progress tracking
• Ensure smooth delivery and stable post-launch operations Education Master degree in field such as Computer Science, Electrical Engineering, Robotics, Automotive Engineering or equivalent Experience Experienced Candidates
• More than 5 years of experience in autonomous driving, vehicle software, or simulation domains
• Minimum 3 years of proven experience as developer focused on ADAS tool chain Fresh Graduates
• Bachelor's, Master’s or above in Computer Science, Automotive Engineering or relevant disciplines
• Keen interest in ADAS tool chain, autonomous driving and simulation technology
• Good logical thinking and learning ability Technical Requirements
• Backend Development & API Engineering: Proficient in at least one backend language (Python, Java, or Go) with strong command of RESTful API design, relational databases, NoSQL databases, and message queues; able to independently develop and maintain high-availability service interfaces
• Containerization & Cloud Operations: Hands-on experience with Docker and Kubernetes for containerized deployment; familiar with multi-cloud environments (public cloud, compliance cloud); capable of independently performing service deployment, monitoring, troubleshooting, and incident resolution in production
• Service Stability Mindset: Strong sense of ownership over production services; experienced in establishing or maintaining monitoring, alerting, and on-call workflows; able to respond rapidly to online incidents and drive root-cause analysis to closure
• Project Coordination & Multi-Tasking: Excellent task decomposition and progress control skills; able to independently manage multiple parallel requirements from intake through delivery, ensuring on-time release and stable operations
• Outstanding analytical thinking and problem-solving skills
• Excellent communication and cross-team collaboration abilities
• Proactive, results-driven working attitude
• Language: Working proficiency in English Preferred Qualifications
• Hands-on experience with autonomous driving data platforms, data closed-loop systems, or annotation platforms
• Proficiency in cloud-native technologies such as Kubernetes, Argo Workflows, and Helm, with production-grade operational experience
• Experience with observability stacks (Prometheus, Grafana, ELK, etc.) for service monitoring and log analysis
• Experience deploying and operating services across public cloud, compliance cloud, or other multi-cloud environments
• Familiarity with ROS, rosbag, and mainstream data formats and processing workflows in the autonomous driving industry