Staff ML Engineer - Embodied AI Scaling Foundations

Job Description At 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. The Data Scaling team owns the Data Flywheel for AV Foundation model development and successive fine tuning. It defines the composition of the data that is needed for the AV to learn behaviors at scale and deliver the driving behaviors necessary for the product success. The team owns the definition and processes for data quality across the data loop. The team directly works on and delivers ML models to the product that successively go up the Data Scaling curves, thereby directly impacting AV product performance through smart use of data. As part of this work, the team builds scalable systems and pipelines that attempt to 10x the data used, its diversity and impact on the models with successive major releases. The team uses existing very large datasets that GM has access to internally as well as defines the [... source excerpt omitted ...] tions. Contribute to the safety, reliability, and scalability of next-generation autonomous vehicles. As a Staff AI/ML Engineer in the Embodied AI Data Foundations organization, you will serve as a senior individual contributor developing machine learning solutions, maximally leveraging multiple sources of data including real and synthetic datasets, that directly impact autonomous driving performance. You will design and implement advanced data curation and model training recipes the will deliver ML models that enabling safe and reliable vehicle behavior across diverse real-world scenarios. In this role, you will partner closely with cross-functional engineering teams, contrib [... source excerpt omitted ...] tion and mentorship. You will help translate research into scalable onboard and offboard ML solutions while contributing to the continuous improvement of our autonomy stack. What You'll Do Design and implement ML solutions aligned with GM’s autonomous driving objectives. Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling/selection, foundation modeling, to solve problems in object detection/tracking/classification, trajectory generation, and safe AI. Collaborate with cross-functional teams to deploy models and algorithms into onboard driving systems. Contribute to applied research efforts and remain current with adv