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. 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.
At NVIDIA, we are building the next generation AI-native autonomous driving architecture — combining classical safety stacks, foundation models, and scalable AI systems into a unified production platform. Autonomous driving is entering a new era. The next generation of AV systems will not be purely classical robotics stacks, nor purely end-to-end neural networks. The future lies in the deep integration of classical safety architectures and large-scale AI-driven systems. If you want to work on problems that build the future of autonomous systems over the next decade, this is the place.
What You’ll Be Doing:
You will compose and build the architecture behind next-generation self-driving vehicle technology.
Work on Prediction, Decision, Planning and Control architecture
Have exposure to Classical safety stack
Build robust system-level safety and fallback strategies
Work on End-to-end data-driven AV pipelines
Hands on experience in DVLA / VA driving models
Develop a World Model–based planning and reasoning model
Have the exposure to engage with Large-scale model inference architecture
Contribute to the integration of innovative research in robotics into our self-driving vehicle technologies.
Deep knowledge of E2E AV software integration from perception through control, including dependencies, interface management, and performance tuning.
What We Need To See:
We’re looking for engineers who can build systems — not just components.
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.
Production experience in autonomous driving systems
Worked on AI foundation models or large-scale ML systems
Helped drive End-to-end driving models
Experience working on Robotics or embodied AI systems
Knowledge and experience in System architecture from 0 → 1 → scale.
Ways To Stand Out From The Crowd:
PhD in a relevant field or related research experience
Knowledge of CUDA is a plus
NVIDIA is widely recognized as one of the world’s most innovative technology companies — driving breakthroughs in AI, autonomous systems, and high-performance computing. As part of our Autonomous Driving division, you’ll work alongside world-class engineers to bring next-generation driving intelligence from research to reality.
Skills Required
- PhD with 4+ years, MS with 6+ years, or BS with 8+ years in Computer Science, Computer Engineering, or related field
- Production experience in autonomous driving systems
- Experience working on AI foundation models or large-scale ML systems
- Experience helping drive end-to-end driving models
- Experience working on robotics or embodied AI systems
- Knowledge and experience in system architecture from 0 -> 1 -> scale
- Deep knowledge of E2E AV software integration from perception through control, including dependencies and performance tuning
- Hands-on experience in DVLA / VA driving models
- Exposure to classical safety stack and ability to build system-level safety and fallback strategies
- Knowledge of CUDA
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
