Staff Machine Learning Engineer - Mapping

Job Description

Our Mapping organization is building national-scale, next-generation mapping systems that move beyond static HD maps toward automated, ML-driven map reconstruction pipelines powered by onboard sensor data. These systems form a critical foundation for localization, perception, simulation, and autonomy at scale.

The Role

We are looking for a Staff Machine Learning Engineer to serve as a technical leader for automated map reconstruction within our Mapping Engineering team.

In this role, you will architect and deliver end-to-end ML and computer vision pipelines that reconstruct, validate, and maintain map primitives (e.g., lanes, boundaries, traffic controls, signs) from large-scale sensor data. Your work will directly power next-generation maps that operate reliably across national deployments and evolving road conditions.

This is a hands-on technical leadership role. You will operate with high autonomy, define technical strategy in ambiguous problem spaces, and lead cross-functional efforts spanning Mapping, Perception, Localization, Simulation, and Infrastructure. You will also mentor senior engineers and help raise the ML and CV bar across the organization.

What You’ll Do (Responsibilities)

• Architect and lead ML-driven map reconstruction systems that operate at national scale using multi-modal sensor data (camera, lidar, radar, vehicle signals).

• Design and implement end-to-end pipelines for offline map reconstruction, including data mining, labeling strategies, model training, evaluation, and production deployment.

• Define technical strategy and system architecture for next-generation mapping capabilities, balancing ML innovation with robustness, safety, and operational scalability.

• Lead the development and adoption of state-of-the-art computer vision and ML techniques (e.g., detection, segmentation, 3D reconstruction, BEV representations) applied to mapping problems.

• Own cross-functional technical initiatives, working closely with Perception, Localization, Simulation, and Platform teams to define interfaces, data contracts, and integration points.

• Drive technical excellence through design reviews, mentorship, and technical guidance for senior and staff-level engineers across teams.

• Diagnose and resolve system-level issues across data pipelines, ML models, and production workflows.

• Serve as a Subject Matter Expert (SME) for ML-based mapping and reconstruction within Mapping and across the AV organization.

• Contribute to technical roadmaps, hiring, and capability building for ML and CV expertise within the Mapping org.

Minimum Qualifications (Must-Have)

• 5+ years of experience building and deploying machine learning or computer vision systems in production environments.

• Strong foundation in computer vision, machine learning, or robotics, with hands-on experience designing and training ML models.

• Proficiency in Python for ML development; familiarity with C++ or other systems languages is a plus.

• Experience building large-scale data pipelines for ML, including dataset curation, labeling workflows, training, and evaluation.

• Proven ability to lead complex, cross-functional technical initiatives with high autonomy and influence.

• BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience.

• Strong systems thinking — ability to reason about end-to-end ML systems, not just individual models.

Preferred Qualifications (Nice-to-Have)

• Experience with mapping, localization, perception, or robotics systems, particularly in autonomous driving or mobile robotics.

• Hands-on experience with 3D perception, BEV representations, or multi-view geometry.

• Familiarity with AV sensor data (camera, lidar, radar) and real-world data challenges (noise, drift, long-tail scenarios).

• Experience deploying ML models into production pipelines with monitorin