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Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027

NVIDIA· Intern
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Shanghai, BeijinginternPosted 1w ago

About the role

Internship role in NVIDIA's autonomous driving team focusing on learning-based driving algorithms, model training/evaluation, data optimization, and multi-carline adaptation.

Responsibilities

  • Develop, train, fine-tune, and evaluate learning-based algorithms for autonomous driving decision-making, planning, and driving behavior.
  • Explore Transformer-based approaches, including VLMs and VLAs, for driving-scene understanding, decision-making, 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, mine hard cases, and improve dataset balance, long-tail coverage, and noise quality.
  • Conduct supervised fine-tuning, reinforcement learning, ablation, and evaluation experiments using offline metrics, open-loop replay, simulation, and vehicle-test results.
  • Support model and carline adaptation across multiple autonomous driving programs, including issue analysis, validation, and scaling.

Qualifications

  • Currently pursuing a Master's or PhD in Computer Science, Artificial Intelligence, Robotics, Mathematics, or a related field.
  • Good Python programming skills and 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, with the ability to collaborate effectively with global teams.
  • Able to work at least three days per week throughout the internship.

Skills

Required:PythonPyTorch or equivalent DL frameworkTransformer architecturesEnglish communicationData workflow tooling
Last updated Oct 16, 2026. Interested? Apply on the company site.

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