Machine Learning Engineer - AI Research (PhD) - Early Career

General Motors is pioneering how cutting-edge machine learning can transform the automotive industry through their AI Research team. As an Early Career Machine Learning Engineer, you will develop end-to-end AI/ML systems for robotics and manufacturing, collaborating with senior engineers and researchers to translate innovative research into practical applications.

Responsibilities

• Adapt machine learning architectures for complex industrial applications, including computer vision, robotic manipulation, predictive maintenance, and process optimization
• Build end-to-end deep learning pipelines that handle multi-modal sensor data (vision, force/torque, proprioception, environmental sensors)
• Contribute to the development of foundation models and transfer learning frameworks that generalize across diverse industrial scenarios and equipment types
• Contribute to the development of data collection and annotation strategies to build high quality datasets for training and validating models in industrial settings
• Work with partner teams to translate technical requirements into ML solutions and support integration efforts
• Own the deployment and monitoring of ML models in production environments
• Publish research findings in top-tier venues (for example, NeurIPS, ICML, CVPR) and contribute to GM’s presence in the research community

Skills

• Currently has, or is in the process of obtaining a PhD in the field of Computer Science, Machine Learning, or a related field (STEM focused), or a Master's degree with significant ongoing AI/ ML contributions. PhD Degree must be completed prior to joining General Motors
• Able to work full time, 40 hours per week
• In depth 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)
• Experience with anomaly detection and predictive maintenance applications through course work, research or projects
• Experience with reinforcement learning for robotic control or process optimization through course work, research or projects
• Experience training multimodal deep learning models
• Demonstrated research contributions in AI/ML technologies through publication of PhD research in top- tier conferences or journals
• Ability to formulate research questions from ambiguous problems and apply rigorous experimental methodology including hypothesis formation, evaluation, and statistical analysis
• Demonstrated track record of publications in top AI/ML conferences or patents demonstrating novel contributions to the field
• Strong programming skills in Python and familiarity with one or more of systems languages (C++/Java)

Benefits

• Medical
• Dental
• Vision
• Health Savings Account
• Flexible Spending Accounts
• Retirement savings plan
• Sickness and accident benefits
• Life insurance
• Paid vacation & holidays
• Tuition assistance programs
• Employee assistance program
• GM vehicle discounts
• Relocation benefits

Company Overview

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