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Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027

NVIDIANVIDIA·Semiconductors

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About the role

Are you looking to be part of a fun, creative company at the forefront of groundbreaking technologies? NVIDIA is leading the way in some of the world's most exciting tech areas, including Virtual Reality, Artificial Intelligence, Deep Learning, and Autonomous Vehicles. We are widely recognized as one of the most desirable employers, with some of the most forward-thinking individuals in the industry working with us. There has never been a more exciting time to join our team!


We are looking for a highly motivated Applied Deep Learning Algorithm Intern to join our autonomous driving team. You will work with experienced engineers on learning-based driving algorithms, supervised fine-tuning, reinforcement learning, data optimization, model evaluation, and multi-carline adaptation.


What You Will Be Doing:

  • 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.

What We Need to See:

  • 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.

Ways to Stand Out from the Crowd:

  • Experience with supervised fine-tuning, imitation learning, reinforcement learning, behavior cloning, or learning-based planning.
  • Experience using or fine-tuning VLMs, VLAs, or other multimodal foundation models.
  • Familiarity with autonomous driving datasets, trajectory data, vehicle logs, simulation, or scenario-mining pipelines.
  • Strong C++ skills or relevant research, open-source, publication, or competition experience.

Skills & Tags

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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • •NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • •The company invests heavily in AI and deep learning, driving technological advancements.
  • •NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • •High competition in the semiconductor industry can impact market share.
  • •Rapid technological changes require constant adaptation and learning.
  • •Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • •The company's AI research is at the forefront of deep learning innovation.
  • •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About NVIDIA

NVDA$226.32-1.29%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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