2026 Fall Intern - Research & Development: AI/ML

Job Description

GM does not provide immigration-related sponsorship for this role.

Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.).

To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report in office three times per week, at minimum [or other frequency dictated by the business]. 

The start date for this internship is September 7, 2026.

The Team

At GM, we craft products people crave and experiences they never forget. It all starts with research and development. We are looking for R&D Interns to craft, design, and develop groundbreaking concepts and technologies that will help shape the future of mobility.

In this internship, you will plan and execute collaborative research that applies advanced artificial intelligence, machine learning, and computational methods to complex vehicle and mobility challenges. Projects may support areas such as vehicle development process acceleration, predictive engineering, vehicle safety, energy and propulsion systems, and next-generation research methods that enable faster, smarter, and more scalable engineering decisions.

You will work with technical leaders across GM Research and Development to explore innovative approaches that combine data, physics-based understanding, and modern AI/ML techniques to solve real-world problems. Our culture of innovation gives you the opportunity to be creative, contribute to impactful research, and help develop technologies that could influence the vehicles and systems of the future.

What You Will Do

• Conduct research and/or experiments to collect required data and validate research ideas
• Apply AI/ML, data science, and computational methods to engineering and research problems
• Support development of methods, models, tools, or workflows that accelerate vehicle development and research outcomes
• Assist with analysis of large, complex datasets to generate insights and improve prediction, automation, or decision-making
• Collaborate with technical teams to evaluate emerging technologies and identify opportunities for application in automotive research
• Document and present results; depending on the assignment, work may lead to external publications and/or intellectual property
• Develop and execute specific research plans, including concept generation, development, implementation, and validation
• Collaborate effectively with peers, management, operations groups, and outside organizations

Required Qualifications

• U.S. citizenship required to comply with federal government contract provision expressly restricting role to U.S. citizens
• Must be currently enrolled in a PhD program
• Pursuing a degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Mechanical Engineering, Robotics, Applied Mathematics, or a closely related science/engineering field
• Strong foundation in AI/ML, statistical modeling, data analysis, or computational methods
• Programming experience in Python and/or other relevant languages for machine learning, analytics, or scientific computing
• Ability to work both independently and in teams
• Consistently demonstrate critical thinking and strong teamwork
• Effective verbal and written communication skills
• Excellent persuasion, active listening, delegation, and leadership skills to work effectively with GM internal and external customers

What Will Give You a Competitive Advantage (Preferred Qualifications)

• Prior research, internship, or project experience applying AI/ML to engineering, physical systems, or large-scale data problems
• Experience with machine learning model development, evaluation, and deployment workflows
• Knowledge and experience of physics-based dynamic system modeling
• Experience with NeruoSymbolic AI or Causal/Explainable AI or Emotion/Affective AI
• Familiarity with generative AI, large language models, deep learning, or physics-informed/data-driven modeling approaches
• Experience working with vehicle, test, simulation, sensor, or other engineering datasets
• Demonstrated ability to translate technical findings into clear recommendations for technic