
location_onGranchina, Calle Guayama, 00917, United States
We're on a mission to build the world's most advanced self-driving vehicles to safely connect people to the places, things, and experiences they care about. At GM's Autonomous Vehicle (AV) organization, we combine cutting-edge research, robust engineering, and large-scale systems to make this future a reality. Our 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.
Our team is developing national-scale, next-generation mapping systems from the ground up, combining robust backend infrastructure with intuitive, performant user interfaces. We are looking for adventure-seekers and imaginative thought leaders to help us transform mobility through technology and ingenuity.
We're looking for a Fullstack Engineer with deep expertise in Frontend technology to join our Mapping Engineering team. You'll be responsible for building web-based tools and interfaces that empower engineers, operators, and stakeholders to interact with our distributed mapping systems. From visualizing map data and pipeline health to enabling map QA and debugging workflows, your work will directly impact the safety and scalability of autonomous driving.
You'll collaborate closely with product managers, backend engineers, machine-learning engineers, and domain experts across Localization, Perception, and Simulation to deliver high-quality, user-centric tools that support the full map lifecycle. This role offers the opportunity to lead frontend development initiatives, define milestones, and mentor engineers across functions while driving technical excellence in UI/UX best practices.
We 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. From day one, we're looking out for your well-being at work and at home so you can focus on realizing your ambitions.
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.
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 and/or a pre-employment screening prior to beginning employment.
General 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, please email Careers.Accommodations@GM.com or call 1-800-865-7580. 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.
Skills: Javascript, Typescript, React, Redux, Zustand, Mapbox GL, Deck.gl, Openlayers, D3.JS, Restful Apis.
Education: Bachelor's Degree in Computer Science or related field, or relevant work experience; BS in Computer Science, Human-Computer Interaction, or related technical field, or equivalent industry experience.
Work model: Hybrid
Granchina, Calle Guayama, 00917, United States
7+ years of experience building and maintaining production-grade frontend applications. Experience with AV mapping systems, HD map data pipelines, or automated cartographic error detection. Knowledge of computer vision or machine learning workflows related to map labeling or perception. Deep experience with Node.js internals and performance tuning. Experience designing performant geospatial services, coordinate systems, and transforms.
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