AI & Hardware Analytics Intern – Data-Driven Production Tech

General Motors; Warren (MI); On-site; USD 90,000 - 97,000; Part time

Benefits offered by this job

Paid US GM Holidays

GM Family Vehicle Discount Program

Growth opportunities

Intern networking events

Job summary

General Motors is seeking an AI/Data Science intern in Warren/Milford, MI to analyze production and quality data and build predictive models for production efficiency. You will work with Python, SQL, and ML tools, and contribute to dashboards for engineering and manufacturing teams.

The internship requires full-time availability (40 hrs/week) and graduation between December 2027 and June 2028. Relocation is handled via permanent address information.

Qualifications

• Pursuing a Bachelor's or Master's degree in a relevant field.
• Coursework or project experience in Python, SQL, MATLAB, statistics, data visualization, or ML.
• Able to work full-time, 40 hours per week.

Responsibilities

• Analyze production, quality, equipment, test, and operational data to identify trends and improvement opportunities.
• Apply statistical analysis, ML, anomaly detection, and AI techniques to support predictive insights and process optimization.
• Develop data pipelines, analytical models, and automated workflows for engineering and production teams.
• Create dashboards, reports, and visualizations to support technical decisions; document methods and findings; present results to engineers and leaders.

Skills

Python

SQL

MATLAB

Statistics

Data Visualization

Machine Learning

Education

Bachelor's or Master's in Data Science/Engineering

Tools

pandas

NumPy

scikit-learn

PyTorch

TensorFlow

Power BI

Tableau

Job description

General Motors is seeking an AI/Data Science intern in Warren/Milford, MI to analyze production and quality data and build predictive models for production efficiency. You will work with Python, SQL, and ML tools, and contribute to dashboards for engineering and manufacturing teams.

The internship requires full-time availability (40 hrs/week) and graduation between December 2027 and June 2028. Relocation is handled via permanent address information.