Jobs / United States / General Motors Company
2027 Summer Intern – Motorsports Aero-Thermal Engineering
General Motors Company · 🇺🇸 Milford, Michigan, United States of America
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What General Motors Company paid sponsored hires in similar roles3 certified filings for “Manufacturing Engineering” (Architectural and Engineering Managers) in MI: $167k–$196k, median $181k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
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. The methods, tools, and insights developed at the racetrack can accelerate production-vehicle engineering, while GM’s production engineering capabilities help advance race-car performance. As an intern, you will work alongside experienced engineers and technical leaders on projects that connect high-performance racing with real-world engineering innovation. What You’ll Do: Example assignments may include: • 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. Projects will be defined by team needs and aligned with the candidate’s experience, interests, and development goals. Required Qualifications: • 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. • Strong analytical and quantitative problem-solving skills grounded in physical principles. • Demonstrated engineering capability through research, coursework, or prior technical projects. • Ability to communicate complex technical findings clearly to both specialized and cross-functional audiences. • Curiosity, initiative, and a commitment to advancing engineering methods and technology. Preferred Qualifications: • Strong interest in motorsports and high-performance vehicle development. • Experience architecting, training, debugging, or evaluating deep-learning models. • Experience using CFD to develop or optimize aerodynamic designs. • Experience with scientific programming, software development, version control, CI/CD, or DevOps practices. • Experience with CAD, geometry processing, meshing, high-performance computing, or engineering data pipelines. • Experience working with experimental data, wind-tunnel