Senior AI/ML Engineer

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.

Are you passionate about pushing the boundaries of multimodal artificial intelligence and seeing your models run on physical, real-world systems? As a Senior Research Scientist specializing in Vision-Language Models (VLMs) and Vision-Language-Action models (VLAs), you will be a key contributor in the AI Research organization. You will focus on advancing the frontier of machine learning to solve complex, open-ended problems in autonomous driving.

In this role, you will design, train, and prototype state-of-the-art foundational models that enable our vehicles to understand complex driving environments, reason through difficult edge cases, and map visual-textual inputs directly to safe driving actions. Your primary challenge will be balancing high-capacity AI reasoning with the stringent latency and compute constraints of onboard vehicle hardware. You will actively contribute to our technical direction, collaborate with deployment teams, and publish your findings at top-tier global AI conferences.

What You’ll Do

• Research, design, and implement advanced Vision-Language Models and Vision-Language-Action models to enhance the autonomous vehicle’s semantic understanding and decision-making capabilities.

• Develop and execute techniques for onboard model optimization, including quantization, distillation, and architecture search, to ensure large foundational models run efficiently on vehicle edge hardware.

• Partner closely with downstream engineering teams (perception, planning, and control) to integrate foundational VLM/VLA outputs into the active vehicle software stack.

• Contribute to the technical roadmap by identifying high-impact research areas and translating strategic machine learning priorities into concrete, actionable prototypes.

• Provide technical mentorship to junior researchers and engineers, fostering a culture of excellence and collaborative innovation.

• Secure intellectual property through patents and represent the company externally by publishing peer-reviewed research at top-tier machine learning conferences.