Autonomous Driving Data & Platform Engineer
Mercedes-Benz · Multiple Locations ·
- Category
- Devops
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 platform architecture design, consolidation engineering, and AI-powered tooling development of the autonomous driving data closed-loop toolchain. This role focuses on four pillars\: building a unified toolchain platform from fragmented standalone tools, scenario management and evaluation infrastructure, AI agent development for autonomous driving R&D, and extensible operator framework construction. The ideal candidate combines strong full-stack platform engineering skills with a keen interest in applying AI/LLM technologies to autonomous driving data workflows
Key Responsibilities
Scenario Management & Evaluation Infrastructure
- Design and maintain the core scenario tree structure to support systematic scenario organization, hierarchical management, coverage tracking, and trend analysis.
- Develop and optimize scenario-specific data statistics and visualization capabilities to improve scenario interpretability and management efficiency.
- Build evaluation pipeline infrastructure including metric definition frameworks, automated report generation, and regression analysis tools to support data quality assessment across the closed-loop workflow.
Toolchain Platform Consolidation
- Foundation Components\: Build core platform infrastructure including environment configuration, logging systems, SSO authentication, and other essential components
- Capability Unification\: Drive the consolidation of fragmented tool capabilities — data decoding, data health checks, data management and retrieval, coarse/fine data selection, ground-truth (GT) production, and data visualization — into a unified one-stop platform
- Platform Migration & Refactoring\: Align with the overall platform roadmap to migrate, integrate, and re-architect existing tools, achieving toolchain standardization and platformization
AI Agent & Intelligent Tooling for Autonomous Driving
- Independently design, develop, and iterate on purpose-built AI agent tools tailored to autonomous driving R&D workflows, including intelligent data quality assessment, automated evaluation metric development, and standardized report generation
- Explore deep integration of large language model capabilities with the data closed-loop toolchain, leveraging intelligent automation to optimize data production, evaluation, and operations end-to-end
- Investigate and prototype AI-driven approaches for scenario mining, badcase analysis, and data selection to significantly boost overall R&D efficiency