Job Description
The Geospatial HD Mapping Engineer will develop and optimize high-definition mapping pipelines, process large-scale LiDAR and camera datasets, and collaborate with teams to deliver accurate geospatial data for autonomous middle-mile logistics operations.
Key Responsibilities
- Design, develop, and expand the HD Mapping production pipeline
- Process, clean, and validate large-scale LiDAR point cloud datasets
- Extract and refine road-based linear and polygonal features
- Annotate and validate 3D objects and roadway furniture
- Perform topology validation of road networks, lane connectivity, and intersection logic
- Develop and maintain Python-based geospatial data processing tools
- Manage and process large spatial datasets using cloud infrastructure
- Work with PostGIS databases for advanced spatial queries
- Support data migration, versioning, and format conversion for mapping data
- Coordinate with remote contributors and internal engineering teams
Requirements
- Bachelor's or Master's degree in Computer Science, Geospatial Engineering, Robotics, Civil Engineering, or a related technical field.
- Minimum 3 years of professional experience in geospatial systems, mapping, or related fields.
- Strong hands-on experience with GIS platforms such as ArcGIS, QGIS, MicroStation, and specialized tools like CloudCompare, MicroStation, OpenCities, TerraSolid, Lidar360.
- Proven experience working with large-scale mapping geospatial production projects and a strong understanding of LiDAR processing workflows.
- Strong Python programming skills.
- Experience with geospatial libraries such as GDAL, Shapely, and GeoPandas.
- Experience with PostGIS, including spatial indexing and query optimization.
- Experience with data formats including OSM, Lanelet, OpenDrive, GeoJSON, LAS, and LAZ.
- Ability to process, clean, and validate large-scale LiDAR point cloud datasets.
- Ability to extract and refine road-based linear and polygonal features, annotate and validate 3D objects and roadway furniture, and perform topology validation of road networks including lane connectivity, intersection logic, and turn constraints.
- Experience developing and maintaining Python-based geospatial data processing tools.
- Experience contributing to performance-critical components, optionally using C.
- Ability to manage and process large spatial datasets using cloud infrastructure, with Azure preferred.
- Experience supporting data migration, versioning, and format conversion for formats such as OSM, OpenDrive, Lanelet.
- Experience working closely with remote freelancers and distributed contributors.
- Ability to work collaboratively with internal teams including autonomy, perception, and planning engineering teams.
- Experience managing Jira tickets, contributing to sprint planning, and providing structured progress reports.
Benefits & Perks
Salary range of $160,000 to $230,000
Work is onsite 5 days a week in Mountain View, CA
Collaborative and inclusive work environment
Opportunities for professional growth and development
Participation in innovative autonomous vehicle projects
Work with cutting-edge geospatial and LiDAR processing technologies
Engagement with a diverse team of experts in autonomous vehicle technology
Ready to Apply?
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