Intern_Automotive Cockpit Edge AI / 边缘AI开发实习生
- 研发工程师
- 梅赛德斯一奔驰（上海）数字技术有限公司
- 上海-浦东新区
[4-6 months, 4-5 days/week]
Name of Project: Global Infotainment Project
Objectives:
We are seeking a motivated Edge AI Intern to join our Base Software OS/AI Infra Development team, who will work on deploying and optimizing AI models directly on local R&D server/automotive hardware to enable real-time, privacy-conscious, and cloud-independent intelligence for next-generation driver and passenger experiences.
Main Tasks:
- Design, train, and optimize lightweight AI/ML models for deployment on a local server/embedded automotive hardware
- Collaborate with software engineers to integrate AI solutions into the vehicle’s Cockpit/ADAS MB.OS
- Benchmark model performance (latency, memory, power efficiency) on edge devices like GPUs, NPUs, or CPU sub-systems
- Explore cockpit on-device AI use cases: natural language GenAi, visual large model, driver monitoring, personalized HMI, or predictive infotainment
- Stay updated on state-of-the-art techniques for edge AI, incl. design & trained model, conversion, quantization, pruning, and federated learning
- Document workflows and present findings to cross-functional teams
Key Learning Opportunities:
- Contribute to AI-driven cockpit features in future MB vehicles
- Work alongside industry experts in automotive software, AI, and MB.OS design
- Access to proprietary datasets, simulation environments, and vehicle prototyping platforms
- Engage with global R&D teams and participate in tech workshops
Key Qualifications:
- Pursuing a Master’s/PhD in CS, AI/ML, Robotics, EE
- Proficiency in Python/C++; familiarity with AI frameworks (TensorFlow, PyTorch, ONNX)
- Strong background in AI, machine learning, and deep learning, focusing on on-device/edge computing
- Familiarity with the implementation principle of large language models for GenAi and their applications
- Experience optimizing models for edge deployment (e.g., CUDA, TensorRT, QNN, or Android Ai core)
- Excellent problem-solving, analytical, and communication skills
Name of Project: Global Infotainment Project
Objectives:
We are seeking a motivated Edge AI Intern to join our Base Software OS/AI Infra Development team, who will work on deploying and optimizing AI models directly on local R&D server/automotive hardware to enable real-time, privacy-conscious, and cloud-independent intelligence for next-generation driver and passenger experiences.
Main Tasks:
- Design, train, and optimize lightweight AI/ML models for deployment on a local server/embedded automotive hardware
- Collaborate with software engineers to integrate AI solutions into the vehicle’s Cockpit/ADAS MB.OS
- Benchmark model performance (latency, memory, power efficiency) on edge devices like GPUs, NPUs, or CPU sub-systems
- Explore cockpit on-device AI use cases: natural language GenAi, visual large model, driver monitoring, personalized HMI, or predictive infotainment
- Stay updated on state-of-the-art techniques for edge AI, incl. design & trained model, conversion, quantization, pruning, and federated learning
- Document workflows and present findings to cross-functional teams
Key Learning Opportunities:
- Contribute to AI-driven cockpit features in future MB vehicles
- Work alongside industry experts in automotive software, AI, and MB.OS design
- Access to proprietary datasets, simulation environments, and vehicle prototyping platforms
- Engage with global R&D teams and participate in tech workshops
Key Qualifications:
- Pursuing a Master’s/PhD in CS, AI/ML, Robotics, EE
- Proficiency in Python/C++; familiarity with AI frameworks (TensorFlow, PyTorch, ONNX)
- Strong background in AI, machine learning, and deep learning, focusing on on-device/edge computing
- Familiarity with the implementation principle of large language models for GenAi and their applications
- Experience optimizing models for edge deployment (e.g., CUDA, TensorRT, QNN, or Android Ai core)
- Excellent problem-solving, analytical, and communication skills
