Senior Machine Learning Engineer - Mapping
$171k - $261k • Sunnyvale, California, United States of America • Full-time
Posted 1mo ago
Job Location
Sunnyvale, California, United States of America
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Our Mapping organization is building next-generation mapping systems that move beyond static HD maps toward automated, algorithmic, and ML-assisted map reconstruction pipelines powered by onboard sensor data. These systems form a critical foundation for localization, perception, simulation, and autonomy at scale. 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. In this role, you will develop the algorithms and data models that reconstruct, conflate, validate, and maintain map primitives from large-scale multi-modal sensor data, owning the geometric and topological correctness of the map itself. This is a hands-on individual contributor role with strong ownership, where 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.
Responsibilities
- 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, road network graphs, and associated map attributes and restrictions.
- Develop large-scale distributed geospatial pipelines to process sensor-derived and third-party road data into production map releases.
- Apply machine learning and computer vision models (detection, segmentation, 3D reconstruction, BEV representations) to automate feature extraction and map change detection, integrating them into production pipelines.
- Build automated quality, validation, and regression systems to identify 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 across geospatial data pipelines, algorithms, models, and production workflows.
- Contribute to design reviews, engineering best practices, and mentorship of engineers.
Requirements
- 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, spatial indexing, geometry operations, map matching, graph algorithms).
- Demonstrated experience designing geospatial data models and working with road network or map data structures.
- Hands-on experience with machine learning or computer vision workflows in production (dataset curation, model training/fine-tuning, evaluation, 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.
Benefits
- Bonus Potential
- Medical insurance
- Dental insurance
- Vision insurance
- Health Savings Account
- Flexible Spending Accounts
- Retirement savings plan
- Sickness and accident benefits
- Life insurance
- Paid vacation & holidays
- Tuition assistance programs
- Employee assistance program
- GM vehicle discounts
- Relocation benefits