Machine Learning Engineer - AI… at General Motors · Mountain…

Summary: General Motors is pioneering how cutting-edge machine learning can transform the automotive industry. As an Early Career Machine Learning Engineer, you will contribute to the development of end-to-end AI/ML systems that solve high-stakes problems in robotics and manufacturing, while collaborating with a world-class team of scientists and engineers. 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 Required Qualifications: - Currently pursuing or has completed a PhD in Computer Science, Machine Learning, or a closely related STEM field, or holds a Master's degree with significant AI/ML contributions with at least one year of relevant industry experience or publications - Able to work full time, 40 hours per week Preferred Qualifications: - 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) Required Skills: Machine Learning, Deep Learning, Python Important Skills: AI/ML Frameworks, Robotics, Predictive Maintenance Nice-to-Have Skills: Research Publication, Statistical Analysis, Problem Formulation 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