Senior Mapping Engineer - Autonomous Vehicles

NVIDIA•Santa Clara, CA

20h

About The Position

We are seeking a Senior Software Engineer to join NVIDIA's Autonomous Vehicle Map Team. The map is the spatio-temporal prior for on-vehicle driving models, enabling autonomous vehicles to continuously improve performance on frequently driven routes. In this role, you will develop and build production-grade on-vehicle map integration solutions. These solutions let perception, localization, and planning use SD/HD maps in real time. You may also contribute to cloud mapping pipelines that generate and maintain these maps. We are looking for outstanding engineers passionate about building intelligent systems for self-driving cars, with expertise in embedded software, real-time systems, and C++ performance optimization. If you're excited about building the systems that enable human-level AI for navigation, this is your opportunity to make an impact.

Requirements

BS or MS degree in Computer Science, Software Engineering, or related field (or equivalent experience)
8+ years of proven experience developing in-vehicle firmware, time-sensitive platforms, or map-to-vehicle integration for autonomous driving
Strong C++ programming skills for performance-critical embedded systems, memory optimization, and real-time constraints
Experience with embedded platforms and real-time operating environments (NVIDIA Orin, Xavier, QNX, or similar)
Understanding of autonomous vehicle software architectures and how maps are consumed by localization, perception, and planning systems
Experience debugging and profiling performance on embedded hardware with memory and timing constraints
Strong Python programming skills for tooling, testing, and automation
Excellent problem-solving skills and ability to debug complex embedded and real-time systems
Experience with Protocol Buffers and efficient data serialization for embedded systems

Nice To Haves

Extensive experience with SD & HD mapping and deep understanding of map data formats
Production experience integrating maps with perception, localization, or planning systems in autonomous vehicles
Expertise in real-time C++ optimization including memory management, cache optimization, lock-free algorithms, and deterministic performance
Experience with computer vision concepts (3D geometry, point clouds, structure-from-motion) and how they relate to map data
Experience with Airflow, Docker, Kubernetes and cloud map pipeline development

Responsibilities

Build C++ modules for in-vehicle map connection with perception, localization, and planning systems to enable real-time map consumption and validate map impact on driving performance
Work with embedded systems and real-time constraints to optimize map parsing, query APIs, and memory management on NVIDIA platforms
Design and implement map query interfaces that provide low latency for lane geometry, routing graphs, and spatial lookups consumed by autonomous driving software
Integrate cloud-generated maps with on-vehicle stacks to enable end-to-end validation of map quality and measure driving performance impact
Develop Python and C++ tools for on-vehicle testing, map data validation, debugging, and performance profiling
Collaborate with perception, planning, and localization teams to understand requirements, build APIs, and ensure maps are accurately accessed by autonomous driving software
Support cloud mapping pipelines (Airflow, Python) for map generation, quality detection, and validation workflows as needed