General Motors is building mapping systems that go beyond static HD maps by using automated and ML-assisted reconstruction pipelines powered by onboard sensor data. In this hybrid role based in Sunnyvale, CA, you will design and deliver mapping algorithms and geospatial data systems that support recurring production map releases, from primitive extraction to validation and release readiness.
This Senior Machine Learning Engineering position focuses on turning multi-modal sensor inputs and road data into reliable map outputs, with quality measures that catch geometric, topological, and semantic defects before they ship.
What you’ll do
- 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 evolve geospatial data models for lane-level connectivity at intersections, road network graphs, and related 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 for detection, segmentation, 3D reconstruction, and BEV representations to automate feature extraction and map change detection, integrating results into production pipelines.
- Create automated quality, validation, and regression systems that identify geometric, topological, and semantic map defects before release, with clear accuracy metrics.
- Work cross-functionally with Perception, Localization, Simulation, and Platform teams to align interfaces, data contracts, and integration points.
- Diagnose and resolve system-level issues across geospatial data pipelines, algorithms, models, and production workflows.
- Participate in design reviews, support engineering best practices, and mentor other engineers on the team.
What you bring
- 3+ years of software engineering experience building production systems, with a substantial portion focused on mapping, geospatial, or geometric algorithms.
- A strong applied foundation in geospatial and computational geometry, including coordinate systems and projections, spatial indexing, geometry operations, map matching, and graph algorithms on road networks.
- Experience designing geospatial data models and working with road network or map data structures, such as lanes, segments, intersections, and 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.
Technology stack
- Python, C++, PostGIS, GeoPandas, GDAL/OGR, S2/H3, OSM, GeoJSON, BEV
Team context
- The Mapping organization is building national-scale, next-generation mapping systems that move beyond static HD maps toward automated, algorithmic, and ML-assisted reconstruction pipelines powered by onboard sensor data.
- These systems provide a critical foundation for localization, perception, simulation, and autonomy at scale.
Compensation
- Salary range: USD 170,600 - 261,300 per year.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits
- Medical, Dental, Vision
- Health Savings Account; Flexible Spending Accounts
- Retirement savings plan
- Sickness and accident benefits
- Life insurance
- Paid vacation and holidays
- Tuition assistance programs
- Employee assistance program
- GM vehicle discounts
Work arrangement and relocation
- This role is categorized as hybrid, with expected reporting to a specific location at least 3 times a week (or other frequency dictated by your manager).
- Relocation benefits are available for candidates who qualify under company policy.
Preferred qualifications
- 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.
About GM
General Motors’ vision is a world with Zero Crashes, Zero Emissions, and Zero Congestion, and it emphasizes responsibility to lead change that makes the world better, safer, and more equitable for all.
Accommodation
General Motors offers opportunities to all job seekers, including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email or call 1-800-865-7580 with a description of the specific accommodation requested, along with the job title and requisition number.
