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’re building the future of autonomous driving — from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: data. Extensive, diverse, high-quality data. We seek a Director of Engineering to guide international teams in Europe and the U.S. who develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world’s most advanced AI platforms.
What You’ll Be Doing:
Lead, encourage, and develop world-class engineering and data teams distributed across Europe and the United States.
Architect and operationalize NVIDIA’s end-to-end data curation strategy, powering AI training, simulation, and continuous AV performance improvements.
Invent and deploy brand new algorithms that mine, classify, and surface the most valuable driving scenarios from massive real-world and simulated datasets.
Collaborate closely with NVIDIA research, AV perception, mapping, simulation, and fleet operations teams to ensure timely, high-fidelity data delivery.
Drive scale: build systems that operate reliably across billions of frames, thousands of edge cases, and diverse sensor configurations.
Champion data quality and metadata standards that accelerate development and improve safety and performance.
What We Need to See:
15+ overall years of industry experience including 5+ years in technical leadership, director-level, or equivalent.
Bachelors degree or equivalent experience.
Demonstrated success leading distributed engineering or data-focused teams.
Deep understanding of algorithm development for data mining, filtering, clustering, or scenario discovery.
Hands-on experience with VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling.
Prior experience in the autonomous vehicle ecosystem — perception, mapping, robotics, ADAS/AD, or AV data workflows.
Strong expertise in large-scale data processing, systems build, or machine learning pipelines.
Strong communication, careful planning, and technical leadership capabilities.
Ways to Stand Out From the Crowd:
Hands-on experience with AV scenario mining, drive replay, or simulation feedback loops.
Experience building automated data quality frameworks or annotation workflows for perception systems.
Ability to drive clarity and alignment across research, engineering, and product leadership.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
You will also be eligible for equity and benefits.
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
- 15+ years of industry experience including 5+ years in technical leadership or director-level roles.
- Bachelor's degree or equivalent experience.
- Demonstrated success leading distributed engineering or data-focused teams.
- Deep understanding of algorithm development for data mining, filtering, clustering, or scenario discovery.
- Hands-on experience with VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling.
- Prior experience in the autonomous vehicle ecosystem (perception, mapping, robotics, ADAS/AD, or AV data workflows).
- Strong expertise in large-scale data processing, systems build, or machine learning pipelines.
- Strong communication, careful planning, and technical leadership capabilities.
- Hands-on experience with AV scenario mining, drive replay, or simulation feedback loops.
- Experience building automated data quality frameworks or annotation workflows for perception systems.
- Ability to drive clarity and alignment across research, engineering, and product leadership.
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.
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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.
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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.
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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.”
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