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 and perception models 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.

What You’ll Do

• 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 evaluate perception models 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 for perception and 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 sensing evaluation workflows
• Participate in code reviews, documentation, and technical discussions to support engineering quality and knowledge sharing.

Your Skills & Abilities

• Bachelor’s or Master’s degree in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
• Experience applying machine learning techniques to real-world systems or large-scale datasets
• Experience building AI/ML or perception systems in autonomy, robotics, computer vision, or related domains
• Proficiency in PyTorch and Python
• Experience working with model training pipelines or large-scale data processing workflows
• Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark
• Experience with model validation, debugging, and failure analysis in ML or perception settings
• Experience with one or more perception domains such as object detection, segmentation, tracking, reconstruction, localization, or sensor fusion
• Ability to collaborate effectively within cross-functional engineering teams.

Preferred Qualifications

• Experience with perception sensors including cameras, radar, and lidar
• Experience with multi-modal sensor fusion and system integration
• Experience with production ML pipelines, model optimization, and performance tuning
• Experience with simulation, synthetic data, or scenario-based evaluation
• Experience with architecting sensory systems or contributing to sensor placement and configuration studies
• Experience deploying ML models into production or working within produ…