Staff Machine Learning Engineer - Mapping

Job DescriptionOur 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 RoleWe 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 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.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. The salary range for this role: is $185,100 to $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. 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.#GM-AV-1 This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. This job may be eligible for relocation benefits. About GMOur vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.Why Join UsWe believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.Benefits OverviewFrom day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.Non-Discrimination and Equal Employment Opportunities (U.S.)General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.AccommodationsGeneral Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, emailus or call us at View phone number on job-api.jobget.com. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.SummaryLocation: Remote - United States; Remote - Washington; Austin, Texas, United States of America; Sunnyvale, California, United States of America; San Francisco, California, United States of America; Warren, Michigan, United States of AmericaType: Full time