Principal Software Engineer, Mapping, Autonomous Vehicles

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $272,000–$431,250 / yr
Employment: Full-time
Posted: 59 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $230k

This role $352k

$137k $463k

below market most similar roles pay here above market

This role pays more than 98% of similar roles. Most pay $204,091–$256,000 — the blue band above. At the midpoint, this role pays about $352k versus about $230k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, Mapping, Autonomous Vehicles

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The Principal Software Engineer, Mapping - Autonomous Vehicles joins a diverse team of engineers in mapping, perception, reconstruction, localization, and autonomous driving. This role involves building scalable mapping systems and offline pipelines that transform crowdsourced perception data and multi-camera video from millions of vehicles into accurate, fresh maps. You will develop 3D reconstruction, structure-from-motion, pose estimation, and multi-view geometry algorithms to handle noisy observations and global consistency constraints. Key responsibilities include building map fusion, change-detection methods, and evaluation metrics for map accuracy and coverage. Required skills include C++, 3D computer vision, SLAM, and experience with sensor data like lidar, radar, and GPS/IMU signals. The work solves the technical problem of creating high-quality map priors to improve driving performance, safety, and coverage for autonomous vehicles.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

C++ 3D Computer Vision 3D Reconstruction Structure from Motion Pose Estimation Multi-view Geometry SLAM Sensor Fusion Lidar Radar GPS IMU Large-scale Systems Map Fusion Change Detection Coordinate Frames Optimization Calibration Autonomous Driving Computer Vision

What you'll do

Build scalable mapping systems using crowdsourced perception data and multi-camera video from a vast fleet of vehicles.
Develop 3D reconstruction, structure-from-motion, pose estimation, and multi-view geometry algorithms for large-scale road scene understanding.
Create map fusion and change-detection methods to handle noisy observations, dynamic scenes, and global consistency constraints.
Build C++ production systems and offline pipelines to transform fleet data into reliable map products for self-driving technologies.
Invent evaluation methods to measure map accuracy, freshness, coverage, consistency, and downstream autonomy impact.
Develop visualization, debugging, and triage tools to identify reconstruction quality issues and fleet data gaps.
Integrate crowdsourced maps into autonomous driving systems by working with perception, localization, and infrastructure teams.

What we're looking for

BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Mathematics, or a related technical field (or equivalent experience).
15+ years of 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 robust to noisy real-world data, dynamic objects, occlusions, incomplete coverage, and long-tail failures.
Experience building maps, localization systems, 3D reconstruction systems, perception systems, or sensor-fusion pipelines for autonomous driving (preferred).

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