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Full Time Nvidia Autonomous Driving Jobs (NOW HIRING)

Nvidia

Semiconductor Safety Engineer

Santa Clara, CA · Hybrid

At NVIDIA, we are building the system, hardware, and software technology which enables autonomous driving. Our safety engineering team is currently looking for a Semiconductor Safety Engineer to help ...

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How much do full time nvidia autonomous driving jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for full time 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 is the difference between Full Time Nvidia Autonomous Driving vs Full Time Nvidia Perception Engineer?

AspectFull Time Nvidia Autonomous DrivingFull Time Nvidia Perception Engineer
Required CredentialsDegree in Computer Science, Electrical Engineering, or related field; experience with AI, deep learning, and automotive systemsDegree in Computer Science, Electrical Engineering, or related field; expertise in perception algorithms, sensor fusion, and computer vision
Work EnvironmentAutomotive industry, R&D labs, autonomous vehicle developmentAutonomous vehicle perception systems, sensor data processing, real-time software development
Employer & Industry UsageNvidia, automotive OEMs, autonomous vehicle startupsNvidia, automotive OEMs, perception-focused autonomous vehicle teams

Full Time Nvidia Autonomous Driving roles focus on developing complete autonomous vehicle systems, including perception, planning, and control. In contrast, Full Time Nvidia Perception Engineers specialize in sensor data processing and perception algorithms. Both roles require similar technical backgrounds but differ in scope, with perception engineers concentrating on sensor fusion and computer vision within the broader autonomous driving ecosystem.

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Full Time Nvidia Autonomous Driving jobs near you
Infographic showing various Full Time Nvidia Autonomous Driving job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 4% As Needed, 5% Full Time, 62% Part Time, 1% Temporary, and 27% Contract. Highlights an 88% Physical, 6% Hybrid, and 6% 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

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

Nvidia Corporation

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 7 days ago

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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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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