Director, Engineering - Autonomous Vehicles

Posted 10 Days Ago
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Santa Clara, CA, USA
In-Office
320K-489K Annually
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Defines the technical vision and architecture for NVIDIA’s next-generation autonomous driving stack, integrating classical safety systems with learning-based autonomy. Leads engineering teams across prediction, planning, control, decision-making, and safety; oversees productionization of end-to-end driving pipelines and foundation models; and partners with research teams to bring robotics, embodied AI, and generative AI advances into scalable autonomous vehicle systems.
Summary Generated by Built In

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 an advanced AI-native autonomous driving architecture. It integrates traditional safety-focused autonomous systems, fully learned driving approaches, foundation models, world models, and scalable AI systems into one 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. We believe the future lies in deeply integrating the strengths of classical, interpretable safety architectures with large-scale learning-based systems. We seek a Director-level technical leader who can define this architecture and build a world-class engineering organization. They will lead the team and drive technology from research and prototypes through production and scale. This leader will work across classical autonomy and modern AI. They will bring together teams and technologies in prediction, planning, control, safety, end-to-end driving, large-scale pre-trained models, and embodied AI. If you want to build the architecture that could define autonomous systems for the next decade, this is the place.


What You’ll Be Doing:

  • Set the technical vision and architecture for NVIDIA’s next-generation autonomous driving stack, spanning both classical and learning-based approaches.
  • Build and lead a high-performing organization of engineers and technical leaders working across Prediction, Decision Making, Planning, Control, and Safety.
  • Define how classical safety-critical autonomy and learned driving systems work together within a unified production architecture.
  • Drive the architecture for robust system-level safety, redundancy, fallback, and degraded-mode strategies.
  • Lead the 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) / driving foundation models and their integration into production autonomous vehicles.
  • Partner closely with research teams to translate breakthroughs in robotics, embodied AI, foundation models, and generative AI into production self-driving technology.

What We Need To See:

We’re looking for a technical and leader who has built systems, teams, and architectures—not just individual components.

  • 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 modern 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 as well as planning and control.
  • Demonstrated ability to attract, recruit, mentor, and grow exceptional engineering talent.
  • Excellent interpersonal skills with a capacity to influence technical experts, executives, researchers, and cross-functional partners.

Ways To Stand Out From The Crowd:

  • Experience building hybrid AV architectures combining 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.

#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 320,000 USD - 488,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 1, 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.

Skills Required

  • PhD with 12+ years, MS with 10+ years, or BS/equivalent experience with 15+ 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 leading senior engineers, architects, and/or engineering managers on sophisticated production systems
  • Extensive knowledge of traditional driverless vehicle systems, including prediction, planning, decision-making, control, safety, redundancy, and fallback systems
  • Strong understanding of learning-based autonomy, including end-to-end driving models, foundation models, large-scale machine learning systems, or embodied AI
  • Experience building end-to-end self-driving systems and understanding perception, planning, and control interactions
  • Demonstrated ability to attract, recruit, mentor, and develop exceptional engineering talent
  • Excellent interpersonal skills and ability to influence technical experts, executives, researchers, and cross-functional partners
  • Experience building hybrid autonomous vehicle architectures combining 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
  • Technical leadership record demonstrated through patents, publications, widely deployed systems, or significant contributions to driverless vehicles, robotics, or embodied AI

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

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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