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Nvidia Drive Av Jobs (NOW HIRING)

Preferred : • Proficiency with AV simulation platforms (e.g., Applied Intuition, IPG Carmaker, NVIDIA DRIVE Sim). • Hands-on experience with Hardware-in-the-Loop (HIL) environments and automotive ...

Proficiency with AV simulation platforms (e.g., Applied Intuition, IPG Carmaker, NVIDIA DRIVE Sim). * HIL/Hardware: Hands-on experience with Hardware-in-the-Loop (HIL) environments and automotive ...

Proficiency with AV simulation platforms (e.g., Applied Intuition, IPG Carmaker, NVIDIA DRIVE Sim). * HIL/Hardware: Hands-on experience with Hardware-in-the-Loop (HIL) environments and automotive ...

Proficiency with AV simulation platforms (e.g., Applied Intuition, IPG Carmaker, NVIDIA DRIVE Sim). * HIL/Hardware: Hands-on experience with Hardware-in-the-Loop (HIL) environments and automotive ...

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Nvidia Drive Av information

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How much do nvidia drive av jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for nvidia drive av in the United States is $53.14, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $66.59 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an NVIDIA DRIVE AV Engineer, and why are they important?

To thrive as an NVIDIA DRIVE AV Engineer, you need a strong background in computer science, robotics, or electrical engineering, with expertise in autonomous vehicle systems and algorithms. Familiarity with NVIDIA DRIVE software stack, deep learning frameworks (such as TensorFlow or PyTorch), and programming languages like C++ and Python is crucial. Excellent problem-solving abilities, teamwork, and effective communication skills distinguish top performers in this role. These skills enable successful development, integration, and optimization of autonomous driving solutions in a fast-evolving industry.

What are some common challenges faced by professionals working with Nvidia Drive AV, and how can they be addressed?

Professionals working with Nvidia Drive AV, an autonomous vehicle platform, often face challenges such as integrating complex sensor data, ensuring algorithm reliability in diverse driving conditions, and keeping up with frequent software updates. Addressing these challenges requires strong collaboration with cross-functional teams including software engineers, hardware specialists, and data scientists. Staying up-to-date through continual learning, leveraging Nvidia’s developer resources, and participating in regular code reviews are effective ways to overcome these hurdles and contribute to the safe deployment of autonomous vehicles.

What is Nvidia Drive AV?

Nvidia Drive AV is an end-to-end autonomous vehicle software platform developed by Nvidia. It provides a comprehensive suite of AI-based technologies for perception, mapping, planning, and control, designed to enable self-driving capabilities in cars. By leveraging deep learning, sensor fusion, and diverse data sources, Nvidia Drive AV helps automakers and developers build, test, and deploy safe and efficient autonomous driving systems. The platform integrates with Nvidia's hardware, such as DRIVE AGX, to deliver high-performance computing required for real-time decision-making on the road.

What is the difference between Nvidia Drive Av vs Nvidia Drive Orin?

FeatureNvidia Drive AvNvidia Drive Orin
Primary UseAutonomous vehicle development and testingAdvanced autonomous driving platform and AI computing
Required CredentialsEngineering degree, experience in automotive or AIEngineering degree, expertise in AI, embedded systems
Work EnvironmentAutomotive R&D labs, testing facilitiesEmbedded systems development, automotive industry
Industry UsageAutonomous vehicle testing and validationProduction autonomous vehicle platforms

While Nvidia Drive Av focuses on autonomous vehicle testing and validation, Nvidia Drive Orin is a more advanced platform used for deploying AI-powered autonomous driving systems in production vehicles. Both roles require similar credentials and work environments but differ in their application stages within the autonomous vehicle development lifecycle.

Senior AI Architect, Foundation Models and SoC Co-Design - Autonomous Vehicles

Senior AI Architect, Foundation Models and SoC Co-Design - Autonomous Vehicles

Nvidia

Santa Clara, CA

Full-time

Posted 3 days ago


Job description

NVIDIA is at the forefront of accelerated computing, AI, and autonomous machines. From generative AI to robotics and self-driving vehicles, our technologies are transforming some of the world's largest industries. NVIDIA DRIVE is redefining autonomous mobility through state-of-the-art AI, high-performance compute, and scalable software-defined architectures.

We are looking for a Senior AI Architect to help define the next generation of AI model paradigms for autonomous vehicles and shape how those models co-evolve with NVIDIA's future embedded SoC architectures. This is a highly strategic role operating at the intersection of frontier AI research, hardware architecture, systems optimization, and autonomous driving. You will work with world-class AI researchers, silicon architects, and AV platform teams to identify the AI workloads that will define the next decade - and ensure NVIDIA platforms are architected to lead them.

What You'll Be Doing:

  • Research and forecast emerging AI model architectures that are expected to shape the future autonomous vehicle stack, including Vision-Language-Action (VLA) models, Multimodal foundation models and more.

  • Drive hardware-software co-design across next-generation AI workloads and NVIDIA embedded SoCs, including GPU, CPU, DLA, memory hierarchy, interconnects, and accelerator subsystems.

  • Analyze compute, memory, bandwidth, and latency characteristics of sophisticated AI architectures such as transformers, diffusion models, or MoE systems

  • Develop architectural insights and influence future NVIDIA silicon, IP, and system-level design decisions through deep workload characterization and performance analysis.

  • Prototype and evaluate emerging model paradigms on NVIDIA DRIVE and embedded AI platforms to validate scalability, efficiency, and deployment feasibility.

  • Partner closely with AI research, autonomous driving software, compiler, runtime, and hardware architecture teams to align long-term roadmap and platform strategy.

  • Evaluate tradeoffs across latency, throughput, power efficiency, safety, and real-time constraints in production AV systems.

  • Define benchmarking methodologies and evaluation metrics for next-generation AV AI systems, including robustness, safety, calibration, and edge-case performance.

What We Need To See:

  • MS, PhD, or equivalent experience in Computer Science, Electrical Engineering, Machine Learning, Robotics, or related field.

  • 12+ years of experience in AI/ML systems, deep learning architecture, or hardware/software co-design.

  • Deep expertise in modern AI architectures and large-scale model systems

  • Experience mapping AI workloads onto heterogeneous compute architectures including GPUs, CPUs, NPUs/DLAs, DSPs, and memory subsystems.

  • Solid understanding of distributed training systems, scaling laws, and inference optimization techniques.

  • Experience with model optimization methods such as quantization, sparsity, pruning, distillation, and memory-efficient inference.

  • Understanding of performance profiling, systems bottleneck analysis, and workload characterization.

Ways To Stand Out From The Crowd:

  • Experience with autonomous vehicle or robotics stacks including perception, planning, prediction, or control.

  • Deep familiarity with NVIDIA platforms such as DRIVE, Jetson, CUDA, TensorRT, Triton, or TensorRT-LLM.

  • Experience influencing silicon architecture or collaborating directly with hardware design teams.

  • Expertise in sophisticated AI efficiency techniques (e.g. FP8/FP4 inference, Mixture-of-Experts routing, Streaming attention and KV-cache optimization)

  • Strong understanding of multimodal fusion across camera, lidar, radar, HD maps, and language inputs.

We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and passionate about building the future of AI and autonomous systems, we want to hear from you. Come join our team and help shape the next generation of AI computing platforms powering autonomous machines worldwide.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 327,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 5, 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