Research and Development Intern - Vehicle Health Management

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. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. 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. To learn more, visit How we Hire.

Accommodations

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