Summer 2027 Intern - Research and Development - Smart Manufacturing Systems

General Motors•Warren, MI

11d•Hybrid

About The Position

The Materials & Manufacturing Systems Research Lab at the General Motors R&D Center is seeking a technically exceptional AI/ML intern with expertise in Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), World Models, and Agentic AI to conduct research in Smart Manufacturing Systems. This role is part of a dynamic team focused on improving GM’s advanced manufacturing capabilities, with assignments expected to provide technical and professional leadership in identifying and developing future strategic applications of AI into GM’s future factory operations. Researchers will also counsel engineering management on process improvements, carry out leadership roles in GM programs/projects, represent GM in research activities with contractors and academic collaborators, and develop a strong record of invention, publishing, and presenting. The Smart Manufacturing Research Group specifically focuses on developing advanced AI/ML, Agentic AI, mathematical modeling, and optimization approaches to build real-time decision support tools for GM plants. Interns will work hands-on to architect, build, deploy, and scale AI/ML models and agents to address complex manufacturing engineering and operations challenges. The ideal candidate should be comfortable developing production-grade AI/ML solutions, evaluating emerging technologies, and engaging senior leaders. A background in manufacturing systems, smart manufacturing, digital twins, simulation, statistics, quality management, control systems, and machine vision is highly desirable, with experience in production operations being a plus.

Requirements

Pursuit of an advanced degree (PhD or Masters) in one of the following areas: Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Engineering, Physics, or a related field.
Must be a current student.
Demonstrated success building and deploying AI/ML models in production or high-value applied research environments.
Deep expertise across multiple AI domains, including machine learning, deep learning, LLMs, generative AI, world models, and physics-based machine learning.
Strong understanding of modern AI/ML development workflows, including data pipelines, model training, evaluation, deployment, monitoring, and lifecycle management.
Experience applying AI/ML to complex technical domains such as engineering, simulation, scientific computing, and advanced manufacturing engineering.
Background in manufacturing process modeling, design, control, and optimization.
Manufacturing engineering theory and principles of production management & operations.
Excellent collaborative skills.
Proven record of high impact publications in peer-reviewed conferences/journals.
Able to work fulltime, 40 hours per week during the summer months.

Nice To Haves

PhD in relevant field of study.
Background in manufacturing process modeling, design, control, and optimization with track record of successful manufacturing implementations.
Proficient in data manipulation, analysis, and visualization.
Structured database design and integration experience along with programming skills (e.g. SQL, C++, Python, R, Matlab).
Familiarity with AI tools: Scikit Learn, Tensorflow, Keras, PyTorch.
Experience with production operations.

Responsibilities

Build, validate, deploy, and scale AI/ML models for high-impact manufacturing engineering, research and development applications.
Conduct technical work across a broad set of AI domains, including classical machine learning, deep learning, GenAI, Large Language Models, multimodal AI, agentic AI, World Models, and physics-based AI.
Translate business and engineering problems into practical AI/ML solution strategies and executable technical plans.
Serve as a technical authority on model development, deployment architectures, data strategy, evaluation methods, and responsible AI practices.
Generate new concepts and ideas while conducting research programs that apply the latest AI/ML tools.
Drive technical assignments in a resourceful and timely manner with minimal supervision.
Work well with fellow researchers, centers, operational groups, plant personnel and universities.
Maintain state-of-art technical skills and knowledge.
Develop working relationships with internal and external subject matter experts.
Effectively communicate and detail results through internal and external publication.
Collaborate with global technical teams and lead discussions as an expert in manufacturing AI/ML.