Design and productionize ML-assisted mapping and geospatial data pipelines for automated map reconstruction and ongoing maintenance.

Design and implement mapping algorithms for map reconstruction and maintenance, including lane and boundary extraction, road network graph construction, map conflation and matching, geometry simplification, and topology validation
Build and iterate geospatial data models for lane-level connectivity at intersections, road network graphs, and related map attributes and restrictions
Develop and scale distributed geospatial pipelines that transform sensor-derived data and third-party road data into recurring production map releases
Apply ML and computer vision models for feature extraction and map change detection, including detection, segmentation, 3D reconstruction, and BEV representations, and integrate outputs into production pipelines
Create automated quality, validation, and regression systems to identify geometric, topological, and semantic map defects before release, with clear accuracy metrics
Partner with Perception, Localization, Simulation, and Platform teams on interfaces, data contracts, and integration points
Troubleshoot and resolve issues across geospatial pipelines, algorithms, models, and production workflows
Participate in design reviews, support engineering best practices, and mentor engineers on the team

3+ years of software engineering experience building production systems, with substantial experience in mapping, geospatial, or geometric algorithms
Strong applied foundation in geospatial and computational geometry, including coordinate systems and projections, spatial indexing, geometry operations, map matching, and graph algorithms for road networks
Experience designing geospatial data models and working with road network or map data structures (lanes, segments, intersections, topology)
Hands-on production experience with machine learning or computer vision workflows, including dataset curation, model training or fine-tuning, evaluation, and deployment
Experience building large-scale distributed data pipelines for geospatial or sensor data
Proficiency in Python and C++
BS or MS in Computer Science, GIS, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience
Ability to own ambiguous, well-scoped technical problems end to end and drive them to production

Experience with HD maps, localization, perception, or robotics systems, especially in autonomous driving or mobile robotics
Hands-on experience with 3D geometry, multi-view geometry, point cloud processing, or SLAM
Familiarity with AV sensor data (camera, lidar, radar) and real-world data challenges such as noise, drift, and long-tail scenarios
Experience with map conflation, change detection, or automated map QA at national or global scale
Experience with geospatial tooling and formats (PostGIS, GeoPandas, GDAL/OGR, S2/H3, OSM, GeoJSON)
Experience deploying ML models into production pipelines with monitoring, validation, and iteration loops
Experience mentoring engineers or acting as a technical lead on a project

Salary range: USD 170,600 - 261,300 per year
Bonus potential: incentive pay program with payouts based on company performance, job level, and individual performance

Hybrid: expected to report to a specific location at least 3 times a week (or other frequency set by the manager)
Relocation benefits available for candidates who qualify under company policy

Mapping organization building national-scale, next-generation mapping systems
Focus on moving beyond static HD maps toward automated, algorithmic and ML-assisted map reconstruction pipelines using onboard sensor data
Mapping systems support localization, perception, simulation, and autonomy at scale

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Senior Machine Learning Engineer - Mapping

Job Description