The board
Internship
Engineering
2027 Summer Intern – Motorsports Aero-Thermal Engineering
General Motors
- Hours
- Full time
- Where
- Milford, Michigan, United States of America
- Posted
- Sep 28
Job Description
The Role:
As a Summer Intern, you will contribute to aerodynamic development within GM Motorsports. Depending on team priorities and your background, your work may involve computational fluid dynamics (CFD), physical testing, automation, data processing, machine learning, or artificial intelligence applications for engineering.
The Team:
GM Motorsports is a high-performance engineering organization competing at the highest levels of global motorsport. Our programs span Cadillac Formula 1, Chevrolet NASCAR and INDYCAR, and Cadillac sports-car racing through IMSA and the LMDh program. Across these programs, our engineers develop and apply expertise in aerodynamics, vehicle performance, simulation, wind-tunnel testing, data science, software, tires, propulsion, and vehicle systems.
Motorsports is a technology test bed for GM.
What you'd do
- Develop and improve CFD workflows across CAD preparation, geometry cleanup, meshing, solver execution, post-processing, and automated reporting.
- Develop tools and methods for wind-tunnel aerodynamic testing, including test planning, instrumentation, data acquisition, controls, and data processing.
- Develop and validate machine-learning or surrogate models that improve aerodynamic performance prediction and flow-field inference.
- Develop AI-enabled tools that improve engineering productivity, accelerate analysis, and support technical decision-making.
- Work with engineers and technical leaders to define requirements, evaluate results, document methods, and communicate recommendations.
- Pursuit of a graduate degree in one of the following areas: physics, mathematics, aerospace engineering, mechanical engineering, computational science, or a closely related field.
- Must be graduating after September 2027 or beyond
- Able to work fulltime, 40 hours per week during the summer months
- Demonstrated experience developing CFD surrogate models, reduced-order models, or other data-driven methods for performance prediction or flow-field inference.
- A strong foundation in one or more of the following areas: mechanical design, aerodynamics, CFD, computer vision, three-dimensional generative design, machine learning, or scientific computing.
- Starts
- 2026-09-28