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

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

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 major vehicle domains, including cockpit, ADAS, body, chassis, and powertrain. This role is highly hands-on, focusing on AI algorithm industrialization, use case deployment, model adaptation, and delivery to mass production.

You will bridge cloud AI, vehicle-side embedded AI, and cross-domain software to build robust, deployable, and vehicle-qualified AI systems. Task Description 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 end-to-end, from requirements definition and technical design through model selection, data preparation, training and fine-tuning, to 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/thermal optimization for automotive So. Cs and domain controllers. Translate research results, open-source models, and prototype algorithms into stable, reliable, automotive-grade AI functions that perform under real-world conditions.

Collaborate closely with cloud platform, hardware, software and testing teams to align architecture, resolve blockers, and accelerate AI feature delivery. Qualifikationen Qualifications 5+ years of hands-on, production-oriented AI engineering experience, with a strong track record in deploying and industrializing AI algorithms for automotive or embedded systems.

OEM or Tier-1 experience is 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 etc., with a solid understanding of vehicle E/E architecture and the automotive software development process. Proven experience in on-vehicle integration, debugging, and problem-solving, with the ability to independently deliver AI features from prototype to mass production.

Excellent cross-team communication, stakeholder alignment, and execution skills, with the ability to drive complex AI architectures into real products. Outstanding analytical and problem-solving skills. Technical leadership and ability to make decisions based on technical facts. Strong sense of ownership and drive. Good communication skills and ability to work in a collaborative, cross-functional environment.

English proficiency in written and spoken form.