Senior AI ML Engineer - Future Sensing, Embodied AI

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 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 Senior AI/ML Future Sensing Engineer in the Embodied AI organization, you will develop and evaluate machine learning solutions contributing to future sensing architecture decisions and autonomous driving performance. You will contribute to designing and improving ML andperceptionmodels that support safe and reliable vehicle behavior across real-world scenarios, while helping connect sensing choices to measurable performance outcomes.

You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready or production-informing solutions while contributing to engineering best practices, technical analyses, and delivery execution.

WhatYou’llDo

Develop and improve AI/ML solutions aligned with GM’s autonomous driving and future sensing objectives

Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling and selection, and foundation modeling to solve problems in object detection, tracking, classification,perception, and safe AI

Develop and evaluateperceptionmodels and components for sensing studies involving cameras, lidar, radar, and multi-modal sensor fusion

Implement and evaluate models, incorporating research advancements into practical applications

Contribute to model training, fine-tuning, validation, debugging, and performance optimization forperceptionand sensor-fusion tasks

Help define and implement robust metrics for detection, reconstruction, localization support, semantic labeling, and model robustness under varied environmental conditions

Work with real and synthetic data to evaluate sensing tradeoffs across weather, lighting, occlusion, sensor noise, clutter, and near-field versus long-range scenarios

Contribute to production pipelines and technical workflows spanning data loading, model evaluation, error analysis, and deployment-oriented support

Collaborate with cross-functional teams to integrate models and algorithms into onboard driving systems and future