Staff ML Engineer - Embodied AI Scaling Foundations

About the role

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 next generation of highest value datasets that GM continues to collect - both from real driving by GM and retail fleets, but also synthetic sim-based datasets. Why Join Us? Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity - into billions+ of examples - across different sources, delivering the maximum value to the model through every additional example. Work with cutting-edge technology and a collaborative, high-impact team of AI/ML engineers, data scientists and engineers who are passionate about leveraging advanced AI techniques to drive innovation for L2, L3 and L4 applications. 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, contribute to core technical direction within your domain, and support the growth of engineers through technical collaboration and mentorship. You will help translate research into scalable onboard and offboard ML solutions while contributing to the continuous improvement of our autonomy stack.

Responsibilities

• 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 advancements in ML frameworks and methods.
• Design and build efficient infrastructure, pipelines, and tooling to facilitate fast-pace model iterations.
• Drive technical execution from prototyping through production deployment, documenting learnings and best practices.
• Support and mentor engineers through technical collaboration and code reviews, fostering knowledge sharing and engineering excellence.
• Your Skills & Abilities
• Bachelor's, Master's, or PhD in Computer Science, Robotics, Machine Learning, or related field.
• Experience working with large-scale foundation models and alignment methods applied to real-world systems.
• Demonstrated ability to deliver applied ML solutions under real-world constraints and timelines.
• Proficiency in PyTorch and Python.
• Experience building and scaling model training pipelines enabling efficient iteration across teams.
• Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark.
• Strong communication skills enabling effective collaboration across engineering teams.
• Experience deploying ML models into production environments and understanding end-to-end deployment workflows.
• Experience in robotics or autonomous driving systems preferred.
• Remote/Hybrid: This role is categorized as fully remote or hybrid.
• 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 repr

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at General Motors? Share your experience