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Nvidia Autonomous Driving Jobs (NOW HIRING)

NVIDIA Corporation

$224 - $357/hr

... driving platforms. The focus is on functional safety of the underlying compute and communications platform on which NVIDIA's autonomous products are built. Do you have a desire to work at the ...

New

Nvidia

Senior System Software Engineer

Santa Clara, CA · On-site

This role works across software, hardware, safety, and product teams to develop, integrate, and improve capabilities within NVIDIA's autonomous driving DRIVE OS software platform. What you'll be ...

Nvidia

Senior System Software Engineer

Santa Clara, CA · On-site

This role works across software, hardware, safety, and product teams to develop, integrate, and improve capabilities within NVIDIA's autonomous driving DRIVE OS software platform. What you'll be ...

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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 Software Engineer - Autonomous Driving

Nvidia

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Re-posted 11 days ago

Key responsibilities

  • Lead architecture and technical strategy for optimizing inference workloads in autonomous driving applications.

  • Drive end-to-end performance analysis across DNN models, TensorRT/compiler flows, CUDA kernels, memory behavior, scheduling, runtime services, and automotive platform constraints.

  • Develop and guide model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, kernel selection, and layout/memory optimization.

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

Our Automotive Platform Team is building the software foundation for scalable, high-performance vehicle computing platforms that power autonomous driving, ADAS, digital cockpit, and centralized vehicle architectures. We are looking for exceptional engineers who thrive on solving deeply complex system-level challenges and shaping the future of automotive computing. We are seeking a Senior Software Engineer for next-generation innovations in automotive platform performance, AI model optimization, scalability, and system architecture.

In this highly visible technical leadership role, you will drive architecture, optimization, and execution across the autonomous driving software stack, with a focus on optimizing and deployment of deep neural networks that are fast, efficient, reliable, and deployable on NVIDIA automotive compute platforms. You will work at the intersection of core platform, deep learning inference, TensorRT and related compiler/runtime technologies, CUDA/GPU performance, model compression, platform software, and safety-aware automotive deployment. What you'll be doing: Lead architecture and technical strategy for optimizing inference workloads in autonomous driving applications.

Drive end-to-end performance analysis across DNN models, TensorRT/compiler flows, CUDA kernels, memory behavior, scheduling, runtime services, and automotive platform constraints. Develop and guide model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, kernel selection, and layout/memory optimization. Collaborate with TensorRT, CUDA, compiler, silicon architecture, perception, planning, DriveOS and safety platform teams.

Build tools, methodologies, and metrics for profiling, benchmarking, debugging, and validating model and platform performance. What we need to see: BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience). 12+ years of software engineering experience in systems software, AI/ML infrastructure, deep learning inference, compiler/runtime technology, or platform performance.

Strong C/C++ and practical Python experience. Deep familiarity with TensorRT, TensorRT-LLM, ONNX, PyTorch, CUDA, Triton, or related frameworks. Experience optimizing DNN models for latency, throughput, memory footprint, and power.

Ways to stand out from the crowd: Hands-on experience with TensorRT internals, CUDA kernels, Triton kernels, or other compiler/runtime technologies. Experience deploying optimized DNNs, LLMs, VLMs, or perception models on embedded, edge, robotics, or automotive platforms. Background in autonomous driving, ADAS, robotics, real-time systems, safety-aware software, or deterministic low-latency systems.

Experience with ISO 26262, QNX, Safe RTOS, DriveOS, Linux, hypervisors, or virtualization. #AutonomousVehicles Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 2, 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

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