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Internship Nvidia Autonomous Driving Jobs (NOW HIRING)

Nvidia

OR · On-site

$110K - $143K/yr

... in Test to help us bring NVIDIA's autonomous vehicle solution out to the world. You will ... field of self-driving cars. You will work with hardworking and dedicated multi-functional ...

Nvidia

OR · On-site

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving teamto design, implement, and deploy cutting-edge end-to-end autonomous driving systems, running on NVIDIA chips in mass ...

Nvidia

OR · On-site

$125K - $172K/yr

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving teamto design, implement, and deploy cutting-edge end-to-end autonomous driving systems, running on NVIDIA chips in mass ...

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How much do internship nvidia autonomous driving jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for internship nvidia autonomous driving in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Nvidia Autonomous Driving vs Intern Nvidia Computer Vision?

AspectInternship Nvidia Autonomous DrivingIntern Nvidia Computer Vision
Required CredentialsEnrolled in Computer Science, Electrical Engineering, or related fields; some knowledge of AI and roboticsEnrolled in Computer Science, Electrical Engineering, or related fields; strong programming skills in Python/C++
Work EnvironmentResearch labs, automotive industry projects, collaborative teamsResearch labs, AI development teams, tech industry settings
Employer & Industry UsageUsed by Nvidia in autonomous vehicle projects and automotive industryUsed by Nvidia in AI and computer vision applications across various sectors

Both internships involve AI, programming, and hardware knowledge, but the Autonomous Driving role focuses on vehicle systems and robotics, while Computer Vision emphasizes image processing and AI algorithms. Candidates should choose based on their interest in automotive applications versus general AI and vision tech.

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Internship Nvidia Autonomous Driving jobs near you
Infographic showing various Internship Nvidia Autonomous Driving job openings in the United States as of May 2026, with employment types broken down into 8% Internship, 50% Full Time, 37% Part Time, and 5% Temporary. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.
Senior Perception Engineer - Autonomous Vehicles

Senior Perception Engineer - Autonomous Vehicles

Nvidia Corporation

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 27 days ago

Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.
We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will work on building world-class 3D obstacle perception solutions based on multi-sensor fusion, including cameras, ultrasonic sensors, and radar, to estimate high-resolution reconstruction of the world. The primary approach will be deep learning. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.
What you'll be doing:
  • Perception experts with application focus will be on multi-sensor fusion based deep learning model development for obstacle perception/fusion in complex driving environments.
  • Applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios.
  • Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization. This includes careful data verification, model architecture design, understanding details of loss function engineering, and being capable of finding detailed ML bugs and iterating toward perfection.
  • Productize the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and SW robustness, with a strong emphasis on production deep learning model development.
  • Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, so that value of data is maximized.

What we need to see:
  • 10+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
  • Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction.
  • Proven experience in production deep learning model development, including careful data verification, model architecture design, loss function engineering, and debugging ML models.
  • Experience in data-driven development and collaboration with data and ground truth teams.
  • Strong programming skills in python and/or C++.
  • Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other.
  • BS/MS/PhD in CS, EE, sciences or related fields (or equivalent experience)

Ways to stand out from the crowd:
  • Experience on end-to-end deep learning model development is a plus.
  • Proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with multi-sensor input.
  • Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.
  • Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic, and sensor fusion principles.
  • Experience with development in CUDA language. The ability to implement CUDA kernels as part of training or inference pipelines.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 10, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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