Quality Control Engineer, HD Mapping

This role is an opportunity to contribute to the quality and reliability of high-definition mapping data used in autonomous trucking. You will review detailed geospatial datasets covering lanes, road boundaries, intersections, signage, and connectivity. Working across mapping, autonomy engineering, and external vendor teams, you will identify defects and help ensure map data meets rigorous accuracy and completeness standards. You will also help develop scalable quality-control workflows, metrics, and sampling strategies as the mapping operation expands. Your work will directly support the readiness of highways, corridors, and operational design domains for autonomous vehicle deployment. The environment is collaborative, technically focused, and centered on building reliable processes for large-scale autonomous systems.

• Bachelor’s degree in GIS, Geomatics, Geography, Surveying, Civil Engineering, Computer Science, or a related discipline, or equivalent practical experience.
• 1–3 years of experience for QC Engineer I or 3–5 years for QC Engineer II in geospatial data quality control, map production, GIS analysis, annotation, or a related quality-focused role.
• Experience working with geospatial data formats such as Shapefiles, GeoJSON, and KML, as well as coordinate and projection systems.
• Familiarity with GIS platforms such as ArcGIS or QGIS and/or LiDAR and point-cloud visualization tools.
• Strong attention to detail and the ability to identify subtle spatial, geometric, and data-quality inconsistencies across large datasets.
• Ability to work with large datasets and develop repeatable, data-driven quality-control processes.
• Strong written communication skills, with the ability to clearly document defects, standards, and findings for both technical and non-technical audiences.
• Ability to collaborate effectively with engineering, operations, and third-party vendor teams.
• For QC Engineer II, experience building or improving QC processes or tooling from the ground up, mentoring junior reviewers, leading vendor or annotator quality calibration, and defining map-quality metrics is expected.
• Preferred experience includes HD mapping for autonomous vehicles or trucking, Lanelet2, OpenDRIVE, or OpenStreetMap, LiDAR point-cloud processing tools such as TerraScan, TerraSolid, or LP360, and scripting with Python or SQL for QC automation or spatial queries such as PostGIS.
• Additional valuable experience includes highway or interstate corridor mapping, managing outsourced annotation teams, and familiarity with functional safety or quality standards such as ISO 26262 or ASPICE.