Sr. Artificial Intelligence and Machine Learning Scientist, Early Career

Work Arrangement :    

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. 

Location:   

Mt. View, California - Mountain View Technical Center  

About the Team:  

Our AI Research team, reporting directly to the Chief AI Officer, is pioneering how cutting-edge machine learning can transform the way vehicles are designed, manufactured, and experienced. We are building the next generation of intelligent systems—integrating multimodal foundation models, generative AI, robotics and predictive maintenance into real-world automotive innovation at global scale.  

The Role:  

As a Senior Machine Learning Engineer, you will lead the development of end-to-end AI/ML systems that solve high-stakes problems in robotics and manufacturing at scale. You will actively participate in the design, prototyping, and deployment of state-of-the-art AI models with direct application to vehicle design, manufacturing operations, robotics, and simulation of physical systems. Beyond technical execution, you will shape and implement GM’s AI research agenda, join a world-class team of scientists and engineers, and represent GM in the global AI community. 

What You’ll Do:  

• 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 

Required Qualifications:  

• PhD in relevant field or related discipline (STEM focused)  

• Post PhD experience in AI/ML, demonstrating advanced AI/ML skill 

• 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 

Preferred Qualifications:  

• Experience with anomaly detection and predictive maintenance applications 

• Experience with reinforcement learning for robotic control or process optimization 

• 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. 

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