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How much do nvidia autonomous driving jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for nvidia 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 types of projects or technologies do employees typically work on within Nvidia Autonomous Driving roles?

Team members in Nvidia Autonomous Driving roles typically work on cutting-edge projects involving development of perception, localization, mapping, planning, and control systems for autonomous vehicles. They often engage with advanced sensor technologies such as lidar, radar, and cameras, and contribute to both software and hardware integration. Collaboration is frequent, with cross-functional work spanning research, engineering, simulation, and validation teams to ensure that autonomous driving solutions are robust and safe. This environment offers ample opportunities for skill expansion and career growth as you work on real-world applications that are transforming the transportation industry.

What is an Nvidia Autonomous Driving job?

An Nvidia Autonomous Driving job involves working on AI, machine learning, and software engineering to develop autonomous vehicle technology. Employees in these roles contribute to perception, planning, simulation, and hardware acceleration to create safer and more efficient self-driving systems. Positions range from software engineers and data scientists to hardware specialists, all focusing on innovation in autonomous mobility.

What are the key skills and qualifications needed to thrive in the Nvidia Autonomous Driving position, and why are they important?

To thrive in an Nvidia Autonomous Driving role, you need strong foundations in computer science, robotics, sensor fusion, machine learning, and software engineering, typically supported by a degree in engineering or related fields. Expertise with tools such as Python, C++, ROS (Robot Operating System), and experience with simulation environments and deep learning frameworks like TensorFlow or PyTorch are commonly required. Effective communication, collaboration, and problem-solving skills help professionals excel while working on complex, multidisciplinary teams. These abilities are crucial for driving innovation, ensuring system reliability, and accelerating the safe deployment of autonomous vehicle technologies.

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Nvidia Autonomous Driving jobs near you
Infographic showing various Nvidia Autonomous Driving job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $44,459 per year, or $21.4 per hour.

Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

Nvidia Corporation

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Re-posted 24 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 244 rated software companies

Job description

We are seeking a Senior Machine Learning Engineer to join our end-to-end autonomous driving team! You will help build, train, and deploy large-scale E2E driving models that leverage VLM/VLA architectures, and build a data flywheel that continuously improves our systems in the real world! 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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What you'll be doing:
  • Designing, implementing, and training large-scale end-to-end driving models.
  • Driving the data flywheel: identifying failure cases, specifying data collection and labeling needs, and iterating models to close real-world performance gaps.
  • Building, curating, and maintaining high-quality multimodal datasets (e.g., video, sensor, language/action traces) tailored for end-to-end autonomous driving.
  • Developing and applying data-centric learning algorithms such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised methods.
  • Exploring and productizing new data sources including simulation, synthetic data, and world-model-based generation/augmentation to improve coverage and robustness.
  • Designing and implementing agentic data workflows that automate data discovery, labeling, evaluation, and retraining to maximize development velocity.
  • Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.

What we need to see:
  • 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
  • Strong background in modern deep learning, including transformer-based architectures, video modeling, and multimodal VLM/VLA or foundation models.
  • Hands-on experience training and deploying deep learning models on real-world datasets: data preprocessing, distributed training, evaluation, debugging, and iterative improvement.
  • Practical experience with at least some data-centric methods such as active learning, curriculum learning, outlier/novelty detection, or large-scale sample mining.
  • Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX), plus solid software engineering practices (testing, code review, CI/CD).
  • Demonstrated ability to collaborate effectively across teams, drive designs from prototype to production, and communicate clearly with technical and non-technical partners.
  • Track record of leading complex cross-team projects, setting technical direction, and making critical technical decisions that impact multiple teams or products.

Ways to stand out from the crowd:
  • Experience building and operating data flywheels or large-scale data pipelines for ML, including data quality monitoring and continuous retraining loops.
  • Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement/imitation learning for driving or robotics.
  • Experience leveraging simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
  • Contributions to sophisticated methods in data-centric ML, VLM/VLA, or autonomous driving, such as impactful publications, open-source projects, or widely used internal tools.
  • Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications.

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 June 13, 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.

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Hours and flexibility

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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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