Senior Machine Learning Engineer - Mapping

Description

The mapping group is building large-scale mapping systems that go beyond static HD maps. They rebuild maps automatically and algorithmically, with machine learning help, from data collected by onboard sensors.

These maps support localization, perception, simulation, and self-driving at scale.

Responsibilities

• Work as a Senior Software Engineer on the Mapping Engineering team, designing and building the algorithms and geospatial data systems that rebuild and maintain maps automatically.
• Write algorithms and data models that rebuild, merge, check, and keep current map elements: lanes, lane links, road graphs, boundaries, traffic controls, and signs, using large volumes of multi-modal sensor data.
• Own the geometry and topology of the map: how features are represented, how sources are combined, and how errors are caught before the vehicle sees them.
• This is a hands-on individual contributor role with real ownership. You take technical problems from start to finish, work closely with Perception, Localization, and Simulation, and use ML where it clearly improves accuracy, coverage, or automation.
• Build lane and boundary extraction, road graph construction, map conflation and matching, geometry simplification, and topology validation.
• Design geospatial data models for lane-level connectivity at intersections, road graphs, and map attributes and restrictions.
• Build distributed geospatial pipelines that turn sensor-derived and third-party road data into production map releases on a regular schedule.
• Apply ML and computer vision, including detection, segmentation, 3D reconstruction, and BEV representations, to automate feature extraction and change detection, and put those models into production pipelines.
• Create automated quality, validation, and regression checks that catch geometric, topological, and semantic defects before release, with clear accuracy metrics.
• Coordinate with Perception, Localization, Simulation, and Platform teams on interfaces, data contracts, and integration points.
• Troubleshoot system problems across data pipelines, algorithms, models, and production workflows.
• Take part in design reviews, set engineering practice, and mentor other engineers.

Requirements

• At least 3 years building production software, mostly on mapping, geospatial, or geometric algorithms.
• Solid grounding in geospatial and computational geometry: 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 structures such as lanes, segments, intersections, and topology.
• Production experience with ML or computer vision: dataset curation, training or fine-tuning, evaluation, and deployment.
• Experience building large-scale distributed pipelines for geospatial or sensor data.
• Proficient in Python and C++.
• BS or MS in Computer Science, GIS, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience.
• Able to take ambiguous but well-scoped technical problems through to production.
• Nice to have: work on HD maps, localization, perception, or robotics, especially autonomous driving or mobile robotics.
• Nice to have: hands-on 3D geometry, multi-view geometry, point cloud processing, or SLAM.
• Nice to have: familiarity with AV sensor data (camera, lidar, radar) and issues such as noise, drift, and rare long-tail scenarios.
• Nice to have: map conflation, change detection, or automated map QA at national or global scale.
• Nice to have: geospatial tools and formats such as PostGIS, GeoPandas, GDAL/OGR, S2/H3, OSM, and GeoJSON.
• Nice to have: deploying ML models with monitoring, validation, and iteration loops.
• Nice to have: mentoring engineers or leading a technical project.

Conditions

Base salary range is $170,600.00 to $261,300.00, with the offer inside that range depending on job-related factors.

This pay range is a good-faith estimate under applicable state law and may not reflect roles outside the California Bay Area.

An incentive pay program pays out based on company performance, job level, and individual performance.

Hybrid role: you report to a specific location at least 3 days a week, or as often as your manager sets.

The company is committed to an inclusive workplace free of unlawful discrimination.

Where applicable, you may need to pass a role-related assessment and/or a pre-employment screening before starting.

Benefits

• Health and wellbeing cover includes medical, dental, vision, HSA, FSA, sickness and accident benefits, life insurance, and an employee assistance program.
• Also offered: a retirement savings plan, paid vacation and holidays, tuition assistance, and company vehicle discounts, among others.
• Relocation support is available to eligible candidates under company policy.