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Nvidia Autonomous Driving Jobs (NOW HIRING)

Nvidia

Senior MLOps Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate endtoend data and ML pipelines for NVIDIA ...

Nvidia

Senior MLOps Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate endtoend data and ML pipelines for NVIDIA ...

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How much do nvidia autonomous driving jobs pay per hour?

As of Sep 6, 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 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 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 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 66% Full Time, 32% Part Time, and 2% 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 MLOps Engineer

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

Want to build the data infrastructure that powers autonomous driving at scale? NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate endtoend data and ML pipelines for NVIDIA's autonomous driving products!

The role builds and operates cloud pipelines that ingest, validate, process, and transform multimodal sensor data from camera, lidar, and radar into training, evaluation, and validation datasets. These pipelines enable NVIDIA's AV program and customerfacing autonomy features. Bring ownership, customer focus, and engineering judgment to scale systems and solve problems across teams.

What You Will Be Doing:

  • Design, build, and operate data pipelines supporting NVIDIA's autonomous driving technology from levels L2 through L4.

  • Own architecture, implementation, and operations for cloud pipelines that ingest, process, label, and validate sensor data.

  • Build observable MLOps systems for model training, ground truth generation, and continuous evaluation at AV scale.

  • Translate customer and program requirements into production systems with perception, ML, data labeling, infrastructure, and product teams.

  • Set technical direction, roadmaps, metrics, and operational benchmarks; deliver against program milestones.

  • Build systems that deliver measurable value to internal and external AV customers.

  • Contribute through design reviews, implementation, debugging, code reviews, and mentorship.

  • Work across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.

What We Need to See:

  • Bachelor's or equivalent experience, Master's, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).

  • 8+ years of engineering experience designing and delivering production distributed systems.

  • Technical leadership as a senior individual contributor delivering largescale systems.

  • Experience with MLOps, data pipelines, and cloud distributed systems.

  • Proficiency in Python and C++ for systemlevel and performancecritical implementation.

  • Experience operating endtoend data or ML pipelines for reliability, scale, and observability.

  • Prior experience in one or more of the following domains: Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPUaccelerated computing.

  • Communication skills that align collaborators and drive execution across functions.

  • A record of ownership, accountability, and customerfocused engineering.

Ways to Stand Out from the Crowd:

  • Experience with AV data platforms handling petabytescale sensor data.

  • Handson contributions to production MLOps or data infrastructure.

  • Experience with automotive or robotic systems, including realworld sensor data pipelines.

  • Background in distributed cloud systems, workflow orchestration, and largescale CI/CD.

  • Familiarity with 3D geometry, perception pipelines, or data generation based on simulated environments.

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 10, 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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Benefits

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

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