Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027

Roboticsconnected; Santa Clara (CA); On-site; USD 48,000 - 83,000; Part time

Job summary

NVIDIA in Santa Clara, CA is seeking an Applied Deep Learning Algorithm Intern for our autonomous driving team. You will work with experienced engineers on learning‑based driving algorithms, fine‑tuning, reinforcement learning, data optimization, and model evaluation.

You should be pursuing a Master's or PhD in CS/AI/Robotics, have Python/PyTorch skills, and be able to collaborate with global teams and work at least three days per week.

Qualifications

• Pursuing a Master's or PhD in CS/AI/Robotics or related field.
• Strong Python skills with PyTorch or similar DL framework.
• Solid understanding of ML, DL, transformers, training, optimization, and dataset analysis.
• Excellent written and spoken English, able to collaborate with global teams.
• Available to work at least three days per week during the internship.

Responsibilities

• Develop, train, fine-tune, and evaluate learning-based autonomous driving algorithms.
• Explore transformer-based approaches for driving-scene understanding, decision-making, and trajectory generation.
• Build data workflows and Python tools for labeling, experiment management, visualization, and evaluation.
• Analyze model failures and vehicle logs, improve dataset balance and data quality.
• Conduct supervised fine-tuning, reinforcement learning, ablation, and evaluation using offline metrics, simulation, and vehicle tests.
• Support model adaptation across multiple autonomous driving programs.

Skills

Python

PyTorch

Machine learning

Deep learning

Transformer architectures

Dataset analysis

English communication

Education

Master's or PhD in Computer Science, Artificial Intelligence, Robotics, Mathematics, or related field

Job description

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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.