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 architectur