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How much do autonomous driving jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for autonomous driving in the United States is $21.37, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.63 per hour, depending on experience, location, and employer.

What is autonomous driving?

Autonomous driving refers to the use of technology to enable vehicles to navigate and operate without direct human input. These vehicles use a combination of sensors, cameras, radar, and artificial intelligence to perceive their environment and make driving decisions. The goal is to improve road safety, reduce human error, and increase transportation efficiency. Autonomous driving systems are typically categorized by levels, ranging from driver assistance to fully self-driving vehicles. This field is rapidly evolving, with ongoing research and real-world testing by automotive and technology companies.

What are some common challenges faced by professionals working in autonomous driving roles?

Professionals in autonomous driving often encounter challenges such as integrating complex sensor data, ensuring the reliability of AI algorithms in unpredictable environments, and meeting strict safety and regulatory standards. Collaboration is key, as teams typically work cross-functionally with hardware, software, and quality assurance groups to solve technical issues and validate system performance. Adapting to rapidly evolving technology and maintaining clear communication across disciplines are essential for success in this dynamic field.

What are the key skills and qualifications needed to thrive in an autonomous driving engineer role, and why are they important?

To thrive as an Autonomous Driving Engineer, you need a solid background in computer science, robotics, and engineering, often demonstrated by a relevant degree and experience in machine learning or computer vision. Proficiency with programming languages such as Python and C++, as well as familiarity with simulation tools, ROS (Robot Operating System), and sensor integration (e.g., LiDAR, radar), is essential. Strong problem-solving abilities, collaboration skills, and adaptability help you effectively tackle complex technical challenges and work within multidisciplinary teams. These skills ensure the development of safe, reliable, and innovative autonomous vehicle systems that meet rigorous industry standards.

What is the difference between Autonomous Driving vs Autonomous Vehicle Software Engineer?

AspectAutonomous DrivingAutonomous Vehicle Software Engineer
Required CredentialsEngineering degrees, specialized training in AI, robotics, or automotive systemsComputer science, software engineering degrees, programming skills in C++, Python
Work EnvironmentResearch labs, automotive companies, testing facilitiesSoftware development teams, automotive tech companies, simulation environments
Industry UsageDeveloping and testing autonomous vehicle systemsDesigning and coding software for autonomous vehicle functions
Common Search/ComparisonYesYes

Autonomous Driving focuses on the overall development, testing, and deployment of self-driving vehicle systems, often involving hardware integration and real-world testing. Autonomous Vehicle Software Engineers primarily concentrate on coding, software design, and algorithm development for autonomous vehicle functionalities. Both roles require technical expertise, but Autonomous Driving is broader, encompassing system integration, while Autonomous Vehicle Software Engineers specialize in software development within the autonomous vehicle industry.

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What cities are hiring for Autonomous Driving jobs?

Cities with the most Autonomous Driving job openings:

What states have the most Autonomous Driving jobs?

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What job categories do people searching Autonomous Driving jobs look for?

The top searched job categories for Autonomous Driving jobs are:

Autonomous Driving jobs near you
Infographic showing various Autonomous Driving job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 31% Part Time, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $44,459 per year, or $21.4 per hour.

Senior Machine Learning Engineer, Perception - Autonomous Driving

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Re-posted 9 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies

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 be driving E2E solutions for perception modules that are responsible for online mapping - including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. 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:

  • Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways.

  • Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.

  • Develop generalizable approaches to support diverse ODDs and Country/region expansion

  • 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, labeling efficiency optimization, so that value of data is maximized

  • Leverage data simulation and augmentation for solving extreme scenarios

  • Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.

What We Need to See:

  • Minimum Requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.

  • 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.

  • 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 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.

Ways to Stand Out from the Crowd:

  • Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras.

  • Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.

  • Proven expertise in deep learning backed up by technical publications in leading conferences/journals.

  • Expertise with Transformers, BEV architectures, and modern static-world perception techniques.Experience in working on similar online mapping and complex road detection problems is a big plus.

Intelligent machines powered by AI are no longer science fiction. GPU Deep Learning has made it possible for self-driving cars to learn, perceive, and reason about the world. NVIDIA GPUs power the algorithms that enable both static world understanding and scalable perception across global road systems. Join us and help define the future of reliable, data-driven autonomous driving.

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 August 22, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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