About the job
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.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
PhD in a relevant field or related research experience
Knowledge of CUDA is a plus