General Motors
Senior Machine Learning Engineer - Mapping
$171K–$261K
Sunnyvale, California, United States of America +3 · Hybrid · Senior · Full-time · Posted Sep 23, 2026
- Location
- Sunnyvale, California, United States of America
Austin, Texas, United States of America
Mountain View, California, United States of America
Warren, Michigan, United States of America - Experience
- 3+ years of production software engineering experience, with a substantial portion focused on mapping, geospatial, or geometric algorithms.
- Education
- BS or MS in Computer Science, GIS, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience.
About the job
Build mapping algorithms, geospatial data systems, and ML-assisted pipelines that reconstruct, validate, and maintain road maps from sensor and third-party data.
What you'll do
- Design mapping algorithms and geospatial models for road features, map reconstruction, conflation, and validation.
- Develop distributed pipelines that process geospatial and sensor data into production map releases.
- Apply ML and computer vision to automate feature extraction and map change detection, and build map quality systems.
What they ask for
- 3+ years of production software engineering experience, with a substantial portion focused on mapping, geospatial, or geometric algorithms.
- Strong applied knowledge of geospatial and computational geometry concepts and road-network graph algorithms.
- Production ML or computer vision workflow experience, plus experience building large-scale distributed geospatial or sensor-data pipelines.
- Proficiency in Python and C++; BS or MS in a related technical field, or equivalent industry experience.
Nice to have
- Experience with HD maps, localization, perception, robotics, 3D geometry, point clouds, or SLAM.
- Experience with geospatial tooling and formats such as PostGIS, GeoPandas, GDAL/OGR, S2/H3, OSM, or GeoJSON.
Pay
$170,600.00 to $261,300.00 USD base salary
Tools
Python, C++, PostGIS, GeoPandas, GDAL/OGR, S2/H3, OSM, GeoJSON
AI focus
Apply machine learning and computer vision—including detection, segmentation, and 3D reconstruction—to automate map feature extraction and change detection, and integrate models into production pipelines.
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