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)
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Architect and lead ML-driven map reconstruction systems that operate at national scale using multi-modal sensor data (camera, lidar, radar, vehicle signals).
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Design and implement end-to-end pipelines for offline map reconstruction, including data mining, labeling strategies, model training, evaluation, and production deployment.
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Define technical strategy and system architecture for next-generation mapping capabilities, balancing ML innovation with robustness, safety, and operational scalability.
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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.
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Own cross-functional technical initiatives, working closely with Perception, Localization, Simulation, and Platform teams to define interfaces, data contracts, and integration points.
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Drive technical excellence through design reviews, mentorship, and technical guidance for senior and staff-level engineers across teams.
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Diagnose and resolve system-level issues across data pipelines, ML models, and production workflows.
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Serve as a Subject Matter Expert (SME) for ML-based mapping and reconstruction within Mapping and across the AV organization.
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Contribute to technical roadmaps, hiring, and capability building for ML and CV expertise within the Mapping org.
Minimum Qualifications (Must-Have)
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5+ years of experience building and deploying machine learning or computer vision systems in production environments.
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Strong foundation in computer vision, machine learning, or robotics, with hands-on experience designing and training ML models.
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Proficiency in Python for ML development; familiarity with C++ or other systems languages is a plus.
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Experience building large-scale data pipelines for ML, including dataset curation, labeling workflows, training, and evaluation.
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Proven ability to lead complex, cross-functional technical initiatives with high autonomy and influence.
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BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience.
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Strong systems thinking — ability to reason about end-to-end ML systems, not just individual models.
Preferred Qualifications (Nice-to-Have)
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Experience with mapping, localization, perception, or robotics systems, particularly in autonomous driving or mobile robotics.
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Hands-on experience with 3D perception, BEV representations, or multi-view geometry.
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Familiarity with AV sensor data (camera, lidar, radar) and real-world data challenges (noise, drift, long-tail scenarios).
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Experience deploying ML models into production pipelines with monitoring, validation, and iteration loops.
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Exposure to simulation-based validation, synthetic data, or map change detection workflows.
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Experience mentoring senior engineers or acting as a technical lead across multiple teams.
Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
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Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
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Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, 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 and more.
Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
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