Director of Engineering - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1

Director of Engineering to lead international teams in developing systems and algorithms for extracting intelligence from petascale autonomous vehicle data, building the data engine for NVIDIA's AI platform. This role focuses on architecting and operationalizing the end-to-end data curation strategy to power AI training, simulation, and AV performance improvements, including inventing new algorithms for data mining and surfacing valuable driving scenarios.

What you'd actually do

  1. Lead, encourage, and develop world-class engineering and data teams distributed across Europe and the United States.
  2. Architect and operationalize NVIDIA’s end-to-end data curation strategy, powering AI training, simulation, and continuous AV performance improvements.
  3. Invent and deploy brand new algorithms that mine, classify, and surface the most valuable driving scenarios from massive real-world and simulated datasets.
  4. Collaborate closely with NVIDIA research, AV perception, mapping, simulation, and fleet operations teams to ensure timely, high-fidelity data delivery.
  5. Drive scale: build systems that operate reliably across billions of frames, thousands of edge cases, and diverse sensor configurations.

Skills

Required

  • 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.

Nice to have

  • 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.

What the JD emphasized

  • petascale fleets
  • massive real-world and simulated datasets
  • billions of frames
  • large-scale data processing
  • machine learning pipelines
  • VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling

Other signals

  • data curation strategy
  • algorithms extracting intelligence from petascale fleets
  • build the data engine powering one of the world’s most advanced AI platforms
  • large-scale data processing
  • machine learning pipelines