1 month ago
Shanghai, ChinaIntern
Responsibilities
- Contribute to distributed data pipelines supporting large-scale Ground Truth generation and global data distribution.
- Integrate international vision, LiDAR, map, and sensor datasets for multi-region model development and validation.
- Develop Ground Truth auto-labeling systems, LLM models, and AI agents.
- Build tools to monitor data quality, job status, and progress within the global Ground Truth release pipeline.
- Support platform scalability, performance tuning, workflow automation, and continuous improvement initiatives.
- Collaborate with global engineering, operations, research, and multidisciplinary teams.
Requirements
- Currently pursuing a BS, MS, or PhD in Computer Science, Software Engineering, Data Engineering, or a related field.
- Solid programming experience with Python and C++.
- Understanding of computer vision, AI agent development, LLMs, and machine learning.
- Analytical and problem-solving abilities with an interest in large-scale AI data ecosystems.
- Good communication and teamwork skills.
- Experience developing AI agents is preferred.
- Experience in Physical AI data engineering or MLOps is preferred.
- Exposure to autonomous-driving data, computer vision, machine-learning pipelines, Physical AI modeling, or Ground Truth data processing is preferred.
Benefits
- Hands-on experience working on real-world, global-scale Physical AI data operations and next-generation autonomous-driving systems.
- Opportunity to collaborate with engineers and scientists across engineering, operations, and research teams.
Categories
Data EngineeringML Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.