Principal Software Engineer, Mapping - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

Principal Software Engineer to build planet-scale maps for self-driving technology using crowdsourced data. The role involves computer vision, geometry, pose estimation, sensor fusion, and large-scale systems, transforming perception signals and video into accurate maps. Focus on building scalable mapping systems, 3D reconstruction, map fusion, and C++ production systems, with a strong emphasis on evaluation methods and debugging tools for autonomous driving applications.

What you'd actually do

  1. Build scalable mapping systems using crowdsourced perception data and multi-camera video collected from a vast number of vehicles.
  2. Develop 3D reconstruction, structure-from-motion, pose estimation, and multi-view geometry algorithms for large-scale road scene understanding.
  3. Build map fusion and change-detection methods that can handle noisy observations, dynamic scenes, imperfect localization, and global consistency constraints.
  4. Build C++ production systems and offline pipelines that transform fleet data into reliable map products used in self-driving and driver support technologies.
  5. Invent evaluation methods to measure map accuracy, freshness, coverage, consistency, and downstream autonomy impact.

Skills

Required

  • Strong programming skills in C++
  • experience building production-quality software systems
  • Solid foundation in 3D computer vision
  • 3D geometry
  • multi-view geometry
  • structure from motion
  • SLAM
  • pose estimation
  • Experience working with large-scale sensor data
  • camera video
  • perception outputs
  • vehicle poses
  • GPS/IMU signals
  • lidar
  • radar
  • map data
  • Ability to reason about coordinate frames
  • calibration
  • uncertainty
  • optimization
  • geometric consistency
  • error propagation
  • Experience crafting algorithms that are robust to noisy real-world data
  • dynamic objects
  • occlusions
  • incomplete coverage
  • long-tail failures
  • Strong debugging and analytical skills
  • ability to inspect data visually
  • build metrics
  • connect system-level failures to algorithmic root causes
  • 15+ years of experience
  • BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Mathematics, or a related technical field (or equivalent experience)

Nice to have

  • Experience building maps
  • localization systems
  • 3D reconstruction systems
  • perception systems
  • sensor-fusion pipelines for autonomous driving or advanced driver assistance systems
  • Background in large-scale mapping
  • crowdsourced map construction
  • map fusion
  • change detection
  • map freshness
  • road topology
  • lane geometry
  • semantic map generation

What the JD emphasized

  • production-quality software systems
  • large-scale sensor data
  • robust to noisy real-world data
  • 15+ years of experience

Other signals

  • autonomous vehicles
  • computer vision
  • large-scale systems
  • 3D reconstruction
  • production systems