LEAD AI Architect (AIOS) LEAD AI 架构师(AIOS)

Mercedes-Benz Group China Ltd.

Mercedes-Benz Group China Ltd., Beijing (Hybrid)

Job Type Full-time

Experience Senior

Posted 3 weeks 2 days ago

Hybrid Senior Level

As a world-leading OEM, Mercedes-Benz seeks experts who are passionate and enthusiastic about applying AI technologies to the automotive industry. We are looking for a self-motivated and knowledgeable architect with a strong background in computer vision, large language models, and their practical applications.

As a Lead AI Architect, you will lead the design, development, and continuous evolution of an end-to-end, vehicle-cloud integrated AI architecture spanning cockpit, ADAS, body, chassis, and powertrain domains. The role focuses on AI algorithm industrialization, use case deployment, model adaptation, and delivery to mass production.

Tasks

Own the end-to-end vehicle-cloud integrated AI architecture, covering the cloud AI platform, on-board AI deployment, cross-domain AI orchestration, closed-loop data, and model lifecycle management.
Drive AI use case implementation from requirements definition and technical design through model selection, data preparation, training and fine-tuning, vehicle-side optimization, integration, calibration, and mass-production release.
Design and optimize cloud-side AI capabilities, including model evaluation, training data preparation, fleet-based model updates, and vehicle-cloud collaborative inference.
Lead on-board AI model adaptation, including quantization, latency optimization, memory tuning, and power and thermal optimization for automotive SoCs and domain controllers.
Translate research results, open-source models, and prototype algorithms into stable, reliable, automotive-grade AI functions.
Collaborate with cloud platform, hardware, software, and testing teams to align architecture, resolve blockers, and accelerate AI feature delivery.

Qualifications

5+ years of hands-on, production-oriented AI engineering experience, preferably in automotive or embedded systems, with OEM or Tier-1 experience highly preferred.
Strong hands-on expertise in model training, fine-tuning, optimization, quantization, and deployment.
Deep understanding of vehicle-cloud integrated AI systems, including cloud training pipelines, model management, on-board deployment, OTA model updates, and closed-loop data systems.
Knowledge of multiple vehicle domains, including cockpit, ADAS/ADS, body, chassis, and powertrain, plus an understanding of vehicle E/E architecture and automotive software development.
Experience with on-vehicle integration, debugging, and problem-solving, with the ability to deliver AI features from prototype to mass production.
Excellent cross-team communication, stakeholder alignment, execution, analytical, and problem-solving skills.
Technical leadership, strong ownership, good communication skills, and the ability to work collaboratively across functions.
English proficiency in written and spoken form.