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Staff Technical Program Manager, Embodied AI. 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 Role: You will serve as a Staff Technical Program Manager responsible for end-to-end delivery of Embodied AI (EAI) model development programs – from research integration through production deployment on next-generation autonomy platforms. In this role, you operate at the intersection of AI research, engineering execution, and product delivery. You translate complex, ML-heavy development efforts into disciplined, predictable execution that results in production-quality systems used in real vehicles, at scale.
Job Responsibility:
Own End-to-End Model Development Execution
Build and Scale Execution Processes for EAI
Own execution across the full Embodied AI model lifecycle, from research transition and model training through evaluation, system integration, validation, and production release
Drive milestone readiness across model training cycles, performance gates, SC3 program milestones, and feature maturity reviews
Partner closely with AI/ML, Evaluation, and Product leads to define clear success criteria, performance metrics, and evaluation frameworks that align technical progress to product outcomes
Deliver clear, concise, and executive‑ready communication on program status, risks, dependencies, and decisions to senior GM leadership
Design, implement, and operate execution mechanisms that enable faster, more predictable Embodied AI delivery
Standardize how Embodied AI initiatives are defined, planned, measured, and delivered across teams and programs
Ensure engineering teams have the data, tooling, clarity, and operational rigor needed to hit performance targets with speed and consistency, without compromising quality or safety
Requirements:
Bachelor’s degree in Computer Science, Engineering, Robotics, or a related technical field, or equivalent practical experience
8+ years of experience in technical program management, engineering program leadership, or closely related roles within software‑ or ML‑intensive environments
Proven track record of leading large‑scale AI/ML, autonomy, or complex software system programs from early concept through production deployment
Strong working knowledge of modern model development workflows, including data ingestion and curation, model training pipelines, evaluation and metrics, deployment, and iteration
Demonstrated ability to operate effectively in highly cross‑functional environments, influencing senior engineering, product, and research leaders to drive execution, resolve tradeoffs, and align priorities
Exceptional communication skills, with the ability to translate complex technical execution into clear, executive‑level narratives around progress, risks, and decisions
Nice to have:
MS or PhD in Engineering, Computer Science, Robotics, Machine Learning, Applied Mathematics, or a related field
Experience working on autonomous driving, ADAS, robotics, or other safety‑critical systems
Familiarity with large‑scale ML infrastructure, including distributed training, compute optimization, data scaling, or evaluation tooling
Experience defining operating rhythms, KPIs, and execution frameworks for ML‑heavy or research‑driven engineering organizations