Director, Engineering - Autonomous Vehicles

NVIDIA•Santa Clara, CA

8d•$320,000 - $488,750

About The Position

NVIDIA is seeking a Director-level technical leader to define the architecture for its next-generation AI-native autonomous driving platform and build a world-class engineering organization. The platform combines traditional safety-focused autonomous systems with learned driving approaches, foundation models, world models, and scalable AI systems. The role spans classical autonomy and modern AI, bringing together teams and technologies in prediction, planning, control, safety, end-to-end driving, large-scale pre-trained models, and embodied AI. The leader will drive technology from research and prototypes through production and scale. The position sets the technical vision and architecture for an autonomous driving stack that integrates classical, interpretable safety architectures with learning-based systems. It leads the development and productionization of end-to-end, data-driven driving pipelines and advances vision-language-action and driving foundation models for production vehicles. The Director will partner with research teams to translate advances in robotics, embodied AI, foundation models, and generative AI into production self-driving technology.

Requirements

PhD with 12+ years, MS with 10+ years, or BS (or equivalent experience) with 15+ overall years of relevant industry experience in Computer Science, Computer Engineering, Robotics, Machine Learning, or a related technical field.
8+ years of experience leading a team.
Significant technical leadership experience, including leading senior engineers, architects, and/or engineering managers working on sophisticated production systems.
Extensive knowledge of traditional driverless vehicle system designs, including prediction, planning, decision making, control, safety, redundancy, and fallback systems.
Solid grasp of learning-based autonomy, including end-to-end driving models, foundation models, large-scale machine learning systems, or embodied AI.
Experience driving end-to-end self-driving system builds and understanding interactions involving perception, planning, and control.
Demonstrated ability to attract, recruit, mentor, and grow exceptional engineering talent.
Excellent interpersonal skills and ability to influence technical experts, executives, researchers, and cross-functional partners.

Nice To Haves

Experience building hybrid autonomous vehicle architectures that combine classical safety systems with end-to-end learned driving.
Experience with VLA frameworks, global representations, foundational architectures, large-scale multimodal systems, or generative approaches to autonomous driving.
Experience with CUDA, GPU computing, and accelerated AI infrastructure.
A record of technical leadership through patents, publications, widely deployed systems, or significant contributions to driverless vehicle technology, robotics, or embodied AI.

Responsibilities

Set the technical vision and architecture for NVIDIA’s next-generation autonomous driving stack, spanning classical and learning-based approaches.
Build and lead a high-performing organization of engineers and technical leaders across Prediction, Decision Making, Planning, Control, and Safety.
Define how classical safety-critical autonomy and learned driving systems work together in a unified production architecture.
Drive architecture for system-level safety, redundancy, fallback, and degraded-mode strategies.
Lead development and productionization of end-to-end, data-driven autonomous driving pipelines, from perception and reasoning through trajectory building and vehicle operation.
Advance large-scale vision-language-action (VLA) and driving foundation models and integrate them into production autonomous vehicles.
Partner with research teams to bring advances in robotics, embodied AI, foundation models, and generative AI into production self-driving technology.
Attract, recruit, mentor, and grow engineering talent.