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NVIDIA

Principal Software Engineer, Mapping - Autonomous Vehicles

Reposted 21 Hours Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
272K-431K Annually
Expert/Leader
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
272K-431K Annually
Expert/Leader
Lead development of planet-scale mapping systems from crowdsourced fleet data. Design and implement 3D reconstruction, SfM, pose estimation, sensor fusion, map fusion, change-detection, and production C++ pipelines. Build evaluation, visualization, and debugging tools, and collaborate with perception, localization, and planning teams to integrate high-quality maps into autonomous driving systems.
The summary above was generated by AI

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.


We seek a passionate team member to build planet-scale maps supporting self-driving technology using crowdsourced data from millions of cars around the world. The role involves computer vision, geometry, pose estimation, sensor fusion, and large-scale systems. You will transform sparse perception signals and dense video clips into accurate and fresh maps. Our work helps autonomous vehicles understand the road with high-quality map priors. These maps improve driving performance, safety, and coverage. You will work with a diverse team of engineers in mapping, perception, reconstruction, localization, and autonomous driving. Together, we will deliver impact to customers worldwide.


What you will be doing:

  • Build scalable mapping systems using crowdsourced perception data and multi-camera video collected from a vast number of vehicles.
  • Develop 3D reconstruction, structure-from-motion, pose estimation, and multi-view geometry algorithms for large-scale road scene understanding.
  • Build map fusion and change-detection methods that can handle noisy observations, dynamic scenes, imperfect localization, and global consistency constraints.
  • Build C++ production systems and offline pipelines that transform fleet data into reliable map products used in self-driving and driver support technologies.
  • Invent evaluation methods to measure map accuracy, freshness, coverage, consistency, and downstream autonomy impact.
  • Develop visualization, debugging, and triage tools to understand reconstruction quality, map issues, localization errors, and fleet data gaps.
  • Work closely with perception, localization, simulation, planning, and infrastructure teams to integrate crowdsourced maps into autonomous driving systems.
  • Relentlessly improve the scale, fidelity, freshness, and reliability of maps built from real-world fleet data.

What we need to see:

  • 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.
  • 15+ years of experience
  • BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Mathematics, or a related technical field (or equivalent experience).

Ways to stand out from the crowd:

  • 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.

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/ 


#AutonomousVehicles

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

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