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Staff ML Infrastructure Engineer - Embodied AI Offboard Perception
General Motors · Flexible / Remote
Publicada em 30/04/2026
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DescriptionAt General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios. As a Staff ML Infra Engineer on the Offboard Perception team within the Embodied AI organization, you will be a senior engineer responsible for developing and deploying offboard machine learning solutions that deliver ground-truth-quality world estimates for multiple partner teams, including onboard model teams, simulation, and evaluation. The models you build will influence every stage of autonomous vehicle development-from training and validation to testing and safety. You will work closely with cross-functional engineering teams, help shape technical direction in your domain, and support other engineers' growth through collaboration and mentorship. You will also help transition research into scalable onboard ML capabilities while continuously improving the autonomy stack. What You'll Do Design, build, and maintain ML infrastructure that enables rapid development, training, evaluation, and deployment of offboard perception models. Own the integration of models into production systems, including packaging, validation, deployment, rollout strategies. Implement CI/CD pipelines for ML systems, including automated testing, model
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