GM's AI Research team is pioneering how cutting-edge machine learning can transform the way vehicles are designed, manufactured, and experienced by building the next generation of intelligent systems.
Requirements
- Expert level knowledge about modern deep learning architectures—Transformers, Diffusion Models, CNNs and model training techniques at scale
- Strong hands-on experience with at least one of the popular AI/ML frameworks (PyTorch, Tensorflow, Keras or JAX)
- Strong programming skills in Python and familiarity with one or more of systems languages (C++/Java)
- Demonstrated track record of publications in top AI/ML conferences or patents demonstrating novel contributions to the field
- Ability to decompose ambiguous problems into tractable research questions and follow rigorous experimental methodology including hypothesis formation, data collection, evaluation and statistical analysis
- Experience with anomaly detection and predictive maintenance applications
- Experience with reinforcement learning for robotic control or process optimization
Responsibilities
- Design and implement novel machine learning architectures for complex industrial applications, including computer vision, robotic manipulation, predictive maintenance, and process optimization
- Develop end-to-end deep learning pipelines that handle multi-modal sensor data (vision, force/torque, proprioception, environmental sensors)
- Create foundation models and transfer learning frameworks that generalize across diverse industrial scenarios and equipment types
- Collaborate with cross functional teams including robotics engineers, SMEs and product teams to understand requirements and translate those to develop ML systems for production systems
- Develop data collection and annotation strategies to build high quality datasets for training and validating models in industrial settings
- Stay current with state-of-the-art methods in ML/AI and share knowledge through internal tech talks and presentations
Other
- This role is categorized as hybrid. This means the successful candidate is expected to report to the office three times per week or any other frequency dictated by the business.
- PhD in relevant field or related discipline (STEM focused)
- Post PhD experience in AI/ML, demonstrating advanced AI/ML skill
- Experience training large scale end-to-end multimodal deep learning models
- Demonstrated research impact in AI/ML technologies either through important publications in top- tier conferences or demonstrated contribution to industry leading systems.
