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
Skills
- 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
- 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
Company Overview
Company H1B Sponsorship
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