Staff Machine Learning Engineer - Mapping

General Motors is building national-scale, next-generation mapping systems for automated, ML-driven map reconstruction. They are seeking a Staff Machine Learning Engineer to lead technical efforts in developing and maintaining mapping systems using large-scale sensor data.

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

Requirements:

• 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
• 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 monitoring, validation, and iteration loops
• Exposure to simulation-based validation, synthetic data, or map change detection workflows
• Experience mentoring senior engineers or acting as a technical lead across multiple teams