Job Description
The Geospatial HD Mapping Engineer is responsible for developing and optimizing high-definition mapping pipelines, processing large-scale LiDAR and camera datasets, and collaborating with engineering teams to support autonomous vehicle navigation and mapping systems.
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 and optimization.
- Support data migration, versioning, and format conversion for geospatial data.
- Coordinate with remote contributors and internal engineering teams to ensure high-quality map delivery.
Requirements
- A Bachelor’s or Master’s degree in Computer Science, Geospatial Engineering, Robotics, Civil Engineering, or a related technical field.
- Minimum of 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.
- 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 using C (optional).
- 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.
- Ability to work closely with remote freelancers and distributed contributors, and collaborate 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 advanced geospatial and LiDAR processing tools
Engagement with cutting-edge autonomous middle-mile logistics technology
Ready to Apply?
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