Research and Development Intern - Vehicle Health Management

General Motors

Warren (MI)

Hybrid

USD 28,000 - 44,000

Full time

6 days ago
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Job summary

General Motors seeks highly motivated interns to join the Vehicle Health Management (VHM) team in Warren, MI. Work at the intersection of connected vehicles, data science, and AI to predict issues before they affect performance. This hybrid internship runs 40 hours per week in the summer, with start dates May 24 and June 14, 2027.

You will help develop diagnostics, prognostics and AI-backed systems, and document results for scalable insights across millions of GM vehicles.

Qualifications

  • Pursuit of an advanced degree (Master or PhD) in Electrical, Mechanical, Aerospace Engineering, CS, AI or related field.
  • Must be a current student.
  • Able to work fulltime, 40 hours per week during the summer months.
  • Background in fault detection, diagnostics and prognostics, root cause analysis.
  • Understanding of AI/ML development workflows across data prep, model training, deployment, eval and monitoring.
  • Experience in Python and ML frameworks PyTorch or TensorFlow, PySpark, MATLAB/Simulink.
  • Effective verbal and written communication skills.
  • Ability to work independently and in teams.

Responsibilities

  • Generate innovative ideas in VHM using physics-based, data-driven and AI modeling.
  • Develop next-generation technologies for vehicle system diagnosis, prognosis and fault-tolerant controls.
  • Develop and execute research plans from concept to evaluation.
  • Document and present results.

Skills

Python
PyTorch
TensorFlow
PySpark
MATLAB/Simulink
AI/ML workflows
Data analysis
Communication
Teamwork
Fault detection

Education

Master's or PhD in Electrical/Mechanical/Aerospace Engineering, Computer Science, AI

Tools

PyTorch
TensorFlow
MATLAB/Simulink

Job description

The Role

We are seeking highly motivated, technically exceptional interns to join our team in the rapidly growing field of Vehicle Health Management (VHM). This is an exciting opportunity to work at the intersection of connected vehicles, data science, physics-based modeling, and advanced AI to develop technologies that make vehicle ownership more convenient and seamless for millions of customers. You will also help advance vehicle and propulsion systems in support of enterprise cost reduction through improved warranty performance and greater engineering development efficiency.

In this role, you will transform vehicle engineering data into actionable insights that can predict system issues and identify root causes before they affect vehicle performance or disrupt customers’ daily lives. Our VHM research combines fundamental physics-based understanding with modern machine learning approaches, including but not limited to large language models, causal AI, and reinforcement learning, to deliver scalable solutions for diagnostics, prognostics, and system performance management.

GM is a leader in this field. One example is the industry-first OnStar Proactive Alert for Starting System, which warns customers of potential component failures before they become emergencies, turning unplanned repairs into scheduled maintenance. Now available on more than 15 million GM vehicles, this service demonstrates the real-world impact of our work at scale. By joining this team, you will help advance technologies that improve the ownership experience for millions of customers.

What You’ll Do:
  • Generate innovative ideas in VHM related areas, utilizing physics-based, data-driven, as well as latest AI-based modeling methodologies
  • Develop next-generation technologies for vehicle system diagnosis, prognosis, and fault-tolerant controls as well as integration
  • Develop and execute specific research plans, including concept generation, prototype development, system implementation, and performance evaluation
  • Document and present results
Required Qualifications:
  • Pursuit of an advanced degree (Master or PhD) in one of the following areas: Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Computer Science, Artificial Intelligence, or related field of study
  • Must be a current student
  • Able to work fulltime, 40 hours per week during the summer months
  • Background in fault detection and isolation, diagnostics and prognostics, root cause analysis
  • Understanding of AI/ML development workflows, including data preparation, model training and deployment, performance evaluation and monitoring
  • Experience in Python (including familiarity with ML frameworks such as PyTorch or Tensorflow), PySpark, MATLAB/Simulink
  • Effective verbal and written communication skills
  • Ability to work both independently and in teams
Preferred Qualifications:
  • Prior internship experience in automotive, technology, or manufacturing
  • Strong critical thinking and analytical skills, especially the ability to synthesize large amounts of data involving multiple variables into comprehensive, impactful insights
  • Strong theoretical and experimental skills, especially in controls, optimization, signal processing
  • Background in latest AI technologies such as deep learning, LLMs, causal AI, reinforcement learning, foundation models, physics-informed machine learning

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.)

The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).

Work Arrangement:

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI three times per week, at minimum.

Start dates for this internship role are in May 24th & June 14th of 2027.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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