Senior Software Engineer, Mapping - Autonomous Vehicles

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

Senior Software Engineer at NVIDIA focused on building planet-scale maps for autonomous vehicles using crowdsourced data. The role involves computer vision, geometry, pose estimation, sensor fusion, and large-scale systems to create accurate and fresh maps that enhance driving performance and safety. Responsibilities include developing reconstruction and fusion algorithms, building production systems, inventing evaluation methods, and developing visualization tools.

What you'd actually do

  1. Build scalable mapping systems using crowdsourced perception data and multi-camera video from millions 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

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

Nice to have

  • Experience building maps, localization systems, 3D reconstruction systems, perception systems, or 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, or semantic map generation.

What the JD emphasized

  • production-quality software systems
  • robust to noisy real-world data

Other signals

  • building planet-scale maps supporting self-driving technology
  • transform sparse perception signals and dense video clips into accurate and fresh maps
  • improve driving performance, safety, and coverage
  • build C++ production systems and offline pipelines that transform fleet data into reliable map products