Staff 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 Staff AI/ML Future Sensing Engineer in the Embodied AI organization, you will serve as a senior individual contributordrivingend-to-end technical work that informs next-generation sensing architecture decisions. You will help define and evaluate machine learning andperceptionsolutions that directlyimpactautonomous driving performance, with emphasis on future sensing architectures, multi-modal sensor fusion, system integration, and the technical evidencerequiredto support sensor and compute decisions. 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 ML andperceptionsolutions while contributing to the continuous improvement of GM s autonomy stack and sensing strategy. WhatYou llDo • Design and implement AI/ML solutions aligned with GM s autonomous driving and future sensing objectives • Lead end-to-end technical studies across sensor selection, sensor configuration, sensor placement, and multi-modal sensor fusion using cameras, lidar, radar, and related sensing modalities • Architect and evaluateperceptionmodels and pipelines for detection, reconstruction, tracking, localization support, semantic labeling, and uncertainty estimation • Drive definition of robust model-level and system-level metrics used to compare sensor configurations, quantify subsystem differences, and evaluate performance parityrelativeto existing architectures • Lead model development efforts spanning data curation, training, validation, performance optimization, debugging, and deployment-oriented analysis • Partner with simulation teams to define synthetic-data and sensor-model requirements needed to evaluate future sensing concepts under adverse weather, sensor noise, occlusions, clutter, and near-field versus long-range scenarios • Drive system integration thinking across sensing, calibration, compute, software architecture, and vehicle constraints • Translate ambiguous architecture questions into concrete experiments, technical recommendations, and clear go / no-go evidence packages • Design and build efficient infrastructure, pipelines, and tooling to support large-scale data processing, model training, evaluation, and rapid iteration across teams • Drive technical execution from prototyping through integration and readiness for production adoption, documentinglearningsand 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, Electrical Engineering, or a related field • Strong experience building and scaling AI/ML systems forperception, autonomy, robotics, or related real-world systems • Deep hands-on experience with modern deep learning frameworks such asPyTorchand strongproficiencyin Python • Experience working with model training pipelines, large-scale data workflows, and infrastructure enabling efficient model iteration across teams • Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark • Strong experience with model validation, debugging, performance optimization, and error analysis under real-world constraints and timelines • Strong experience with multi-modal sensor fusion andperceptionpipelines using cameras, radar, lidar, or related sensing modalities • Experience defining metrics and evaluation methodologies forperceptionor autonomy systems • Strong communicationskills enabling effective collaboration across engineering teams • Experience deploying or preparing ML models for production environments and understanding end-to-end deployment workflows. Preferred Qualifications • Experience in robotics or autonomous driving systems • Experience with architecting perception or sensory systems for automotive, robotics, or safety-critical platforms • Experience with system integration across sensors, calibration, c...