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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 Engineer within the Onboard Embodied AI organization, you will be a senior individual contributor driving cutting-edge end-to-end machine learning solutions directly impacting autonomous driving performance. Your role is pivotal in designing, architecting, and deploying advanced ML models that translate raw sensor data into actionable driving behaviors, enabling vehicles to robustly navigate diverse real-world scenarios and conditions. You'll lead critical technical initiatives, collaborate closely with cross-functional teams, mentor ML engineers, and significantly shape the future of onboard ML capabilities. The Onboard Embodied AI team is at the forefront of developing groundbreaking onboard ML systems powering fully autonomous vehicles. We leverage modern end-to-end machine learning approaches with sophisticated neural networks trained from large-scale driving data and using state-of-the-art alignment approaches. Our solutions enable vehicles to understand complex, dynamic driving environments, handle uncertainty gracefully, and adapt seamlessly to changing conditions. Join a collaborative and innovative team redefining autonomy through state-of-the-art machine learning, delivering solutions that move beyond current technological boundaries.
Job Responsibility:
Drive the design, development, and deployment of advanced onboard ML models, delivering end-to-end solutions capable of real-time inference and robust autonomous driving performance
Lead and architect complex machine learning projects, from conception through validation to onboard implementation, emphasizing scalability, robustness, and safety-critical operation
Champion innovation in neural network architectures, training methodologies, and inference optimization strategies suited for real-time onboard deployment
Provide technical mentorship and thought leadership, elevating engineering practices, and fostering ML innovation across teams
Collaborate closely with multidisciplinary engineering groups, ensuring seamless integration of ML capabilities into autonomous vehicle systems
Influence technical roadmaps, shaping strategic ML priorities aligned with company objectives and product milestones
Requirements:
Master's or Ph.D. in Machine Learning, Robotics, Computer Science, Electrical Engineering, or a related technical field
4+ years of experience working with large-scale Foundation Models, including LLMs, VLAs and vision-focused models
Extensive experience developing and deploying advanced ML systems, particularly in end-to-end real-time onboard applications
Proven track record as a technical expert in developing robust deep learning models that directly map sensor data to actionable outputs within safety-critical systems
Deep expertise in state-of-the-art computer vision techniques, neural architectures, representation learning, real-time inference, model optimization, and robustness under uncertainty
Strong software engineering proficiency, particularly Python and C++, alongside extensive hands-on experience with modern ML frameworks (PyTorch, TensorFlow, JAX)
Excellent communication, collaboration, and mentoring abilities, comfortable influencing technical strategy and guiding ML engineering excellence across the organization
Nice to have:
AV/ADAS experience is a big plus
What we offer:
An incentive pay program offers payouts based on company performance, job level, and individual performance
This job may be eligible for relocation benefits
Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate