onsite
Senior ML Engineer - Embodied AI Onboard Autonomy - General Motors
ML Engineer
Lead the design and deployment of advanced machine‑learning models for embodied AI systems that enable autonomous vehicle perception and decision‑making, leveraging Python, C++, ROS, and deep learning frameworks to deliver safe, real‑time onboard solutions.
About the role
Key Responsibilities
- Architect, develop, and optimize ML pipelines for embodied AI in autonomous vehicles, ensuring real‑time performance and robustness.
- Collaborate with cross‑functional teams to integrate perception, planning, and control modules using ROS and C++.
- Design and train deep learning models for sensor fusion, object detection, and trajectory prediction, utilizing Python and popular frameworks.
- Implement rigorous testing, validation, and continuous integration workflows to maintain safety and reliability standards.
- Mentor junior engineers and contribute to knowledge sharing across the AI and software engineering communities.
Requirements
- 10+ years of experience in machine learning and autonomous systems engineering.
- Proficiency in Python, C++, and ROS with a strong background in deep learning frameworks (TensorFlow, PyTorch).
- Deep understanding of embodied AI concepts, sensor fusion, and real‑time inference on embedded platforms.
- Experience with large‑scale data pipelines, model deployment, and performance optimization.
- Excellent problem‑solving skills and a passion for advancing autonomous vehicle technology.
Skills
machine learningpythoncrosdeep learning