below marketmost similar roles pay hereabove market
This role pays more than
98%
of similar roles. Most pay
$216,300–$288,150
— the blue band above.
At the midpoint, this role pays about
$404k
versus about
$252k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
Director, Engineering - Autonomous Vehicles joins the engineering team to lead the development of an advanced AI-native autonomous driving architecture. This leader will define the technical vision for a production platform that integrates classical safety-focused autonomous systems with fully learned driving approaches, foundation models, and world models. Key responsibilities include building a high-performing organization of engineers to work across prediction, planning, control, safety, and end-to-end driving. The role requires driving the productionization of data-driven pipelines and advancing vision-language-action foundation models. Candidates must possess expertise in traditional driverless vehicle system designs, large-scale machine learning systems, and embodied AI. Technical skills include experience with CUDA, GPU computing, and accelerated AI infrastructure to solve the complex problem of merging interpretable safety architectures with large-scale learning-based systems.
Set the technical vision and architecture for the next-generation autonomous driving stack.
Build and lead a high-performing organization of engineers across prediction, planning, control, and safety.
Define the integration of classical safety-critical autonomy with modern learned driving systems.
Drive the architecture for system-level safety, redundancy, fallback, and degraded-mode strategies.
Lead the productionization of end-to-end, data-driven autonomous driving pipelines.
Advance large-scale vision-language-action models and integrate them into production vehicles.
Translate research breakthroughs in robotics and generative AI into production self-driving technology.
What we're looking for
Hold a PhD with , MS with , or BS with relevant industry experience in Computer Science, Computer Engineering, Robotics, or Machine Learning.
Have 8+ years of experience leading a team.
Possess significant technical leadership experience leading senior engineers, architects, and engineering managers on sophisticated production systems.
Demonstrate extensive knowledge of traditional driverless vehicle system designs including prediction, planning, decision making, control, safety, redundancy, and fallback systems.
Possess a solid grasp of modern learning-based autonomy, including end-to-end driving models, foundation models, large-scale machine learning systems, or embodied AI.
Have experience driving end-to-end self-driving system builds and understanding interactions involving perception, planning, and control.
Demonstrate the ability to attract, recruit, mentor, and grow exceptional engineering talent.
Experience building hybrid AV architectures combining classical safety systems with end-to-end learned driving (preferred).