Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027
Salary not listed • China, Shanghai • Internship
Posted 18d ago
Job Location
China, Shanghai
Tech Stack
Remote Work Policy
On-site
Employment Type
Internship
Categories
LLM Engineer
About the job
NVIDIA is seeking a highly motivated Applied Deep Learning Algorithm Intern to join its autonomous driving team. This internship offers the opportunity to work with experienced engineers on cutting-edge learning-based driving algorithms. You will contribute to areas such as supervised fine-tuning, reinforcement learning, data optimization, model evaluation, and adapting models for various vehicle lines. This role is ideal for individuals passionate about groundbreaking technologies in AI and autonomous vehicles, looking to gain hands-on experience in a creative and forward-thinking environment.
Responsibilities
- Develop, train, fine-tune, and evaluate learning-based algorithms for autonomous driving decision-making, planning, and behavior.
- Explore Transformer-based approaches, including VLMs and VLAs, for driving-scene understanding and trajectory generation.
- Build supervised fine-tuning data workflows and Python tools for scenario mining, data cleaning, filtering, labeling, experiment management, visualization, and model evaluation.
- Analyze model failures and vehicle logs to improve dataset balance, long-tail coverage, and noise quality.
- Conduct supervised fine-tuning, reinforcement learning, ablation, and evaluation experiments using various metrics and simulation.
- Support model and carline adaptation across multiple autonomous driving programs, including issue analysis, validation, and scaling.
Requirements
- Currently pursuing a Master's or PhD in Computer Science, Artificial Intelligence, Robotics, Mathematics, or a related field.
- Good Python programming skills.
- Hands-on experience with PyTorch or another deep learning framework.
- Good understanding of machine learning, deep learning, Transformer architectures, model training, optimization, and dataset analysis.
- Proficient English communication skills, both written and verbal.
- Ability to collaborate effectively with global teams.
- Able to work at least three days per week throughout the internship.