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

GM•Mountain View, CA

2d•Hybrid

About The Position

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. 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 at scale. You will work closely with senior engineers and researchers to design, prototype, and deploy state-of-the-art AI models with direct application to vehicle design, manufacturing operations, robotics, and simulation of physical systems. You will have the opportunity to translate cutting-edge research into production systems, collaborate with a world-class team of scientists and engineers, and grow your expertise while contributing to GM's AI research agenda and engaging with the broader AI community.

Requirements

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 Motor s
Able to work full time, 40 hours per week

Nice To Haves

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)

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

Benefits

GM offers a variety of health and wellbeing benefit programs.
Benefit options include 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 and more.
This job may be eligible for relocation benefits.

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