Jobs / United States / General Motors Company
Summer 2027 Intern - Research and Development - Smart Manufacturing Systems
General Motors Company · 🇺🇸 Warren, 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 roles35 certified filings for “Manufacturing Engineer” (Industrial Engineers) in MI: $123k–$139k, median $132k. Most were filed at wage level IV (77%) — 4 lottery entries, ≈61% 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.
Or apply yourself on the official page →
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: The Materials & Manufacturing Systems Research Lab at the General Motors R&D Center located in Warren, Michigan is seeking a technically exceptional AI/ML intern with world class, Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), World Models, and Agentic AI skills to perform leading edge research in the area of Smart Manufacturing Systems. This is an exciting growth area at GM R&D where researchers will be part of a dynamic team focused on improving GM’s advanced manufacturing capabilities. Assignments will vary depending on background, but they will be expected to provide immediate technical and professional leadership in assignments to identify, define, and develop future strategic applications of AI into GM’s future factory operations. Researchers are also expected to counsel GM engineering management on manufacturing engineering process, practice and tool improvements, as well as carry out leadership roles in GM programs and/or projects. They will likely represent GM in a variety of research activities with contractors and academic collaborators, and at other GM Centers, and external agencies and technical organizations. In addition, researchers are expected to develop a strong record of invention, publishing and presenting. The specific research focus of the Smart Manufacturing Research Group is to develop advanced AI/ML, Agentic AI, mathematical modeling and optimization approaches and build real-time, decision support tools that enable GM’s plants to meet efficiency and quality goals. In this role, you will work hands-on to architect, build, deploy, and scale AI/ML models, agents, agentic systems that address complex manufacturing engineering and operations challenges. The ideal candidate is comfortable developing production-grade AI/ML solutions, evaluating emerging technologies, and engaging senior leaders in clear, actionable discussions on strategy, roadmap, and business impact. A background in manufacturing systems and process design, smart manufacturing, digital twins, simulation, statistics, quality management, control systems and machine vision would also be highly desirable. Experience with production operations is a plus. What You’ll Do: 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 Required Qualifications: • 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 produc