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# Senior Machine Learning Engineer - Mapping

- **Company:** General Motors
- **Location:** Warren, MI, United States
- **Experience:** Expert
- **Salary:** $170,600.0 - $261,300.0
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Computer Vision, C++ (Programming Language), Data Structures, Distributed Data Store, Python (Programming Language), Machine Learning, Performance Tuning, PostGIS, Computational Geometry, Software Engineering, Build Management, Information Technology, Geospatial Data Abstraction Library (GDAL), Machine Learning Operations, Feature Extraction
- **Published:** September 25, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3404621726&tx=VT7166THI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 3+ years of software engineering experience building production systems, with a substantial portion focused on mapping, geospatial, or geometric algorithms.
 * Strong applied foundation in geospatial and computational geometry concepts - coordinate systems and projections, spatial indexing, geometry operations, map matching, and graph algorithms on road networks.
 * Demonstrated experience designing geospatial data models and working with road network or map data structures (lanes, segments, intersections, topology).
 * Hands-on experience with machine learning or computer vision workflow in production - 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, particularly 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.
 * 3+ years of software engineering experience building production systems, with a substantial portion focused on mapping, geospatial, or geometric algorithms.

## Description

We are looking for a Senior Software Engineer to design and build the mapping algorithms and geospatial data systems behind automated map reconstruction and maintenance within our Mapping Engineering team.

In this role, you will develop the algorithms and data models that reconstruct, conflate, validate, and maintain map primitives - lanes, lane connectivity, road network graphs, boundaries, traffic controls, and signs - from large-scale multi-modal sensor data. You will own the geometric and topological correctness of the map itself: how features are represented, how disparate sources are merged, and how errors are detected before they reach the vehicle.

This is a hands-on individual contributor role with strong ownership. You will drive technical problems end to end, partner closely with Perception, Localization, and Simulation, and apply machine learning where it measurably improves accuracy, coverage, or automation rate.

What You'll Do (Responsibilities)

 * Design and implement mapping algorithms for map reconstruction and maintenance - lane and boundary extraction, road network graph construction, map conflation and matching, geometry simplification, and topology validation.
 * Build and evolve geospatial data models for lane-level connectivity at intersections, road network graphs, and associated map attributes and restrictions.
 * Develop large-scale distributed geospatial pipelines that process sensor-derived and third-party road data into production map releases on a recurring cadence.
 * Apply machine learning and computer vision models - detection, segmentation, 3D reconstruction, BEV representations - to automate feature extraction and map change detection, and integrate them into production pipelines.
 * Build automated quality, validation, and regression systems that catch geometric, topological, and semantic map defects before release, with clear accuracy metrics.
 * Collaborate cross-functionally with Perception, Localization, Simulation, and Platform teams on interfaces, data contracts, and integration points.
 * Diagnose and resolve system-level issues spanning geospatial data pipelines, algorithms, models, and production workflows.
 * Contribute to design reviews, engineering best practices, and mentorship of engineers on the team., This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.