General Motors
Summer Intern - AI & Hardware Analytics - Adpt
USA internshipsAI/ML/DataPosted 20 days ago
- Location
- Milford, MI +1
- Type
- USA internships
Apply nowOpens General Motors’s application page
General Motors
From General Motors’s careers page.
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.)
To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.
On-Site: This internship is categorized as on-site. The selected intern is expected to report to the office 5 days a week.
Warren, MI
Milford, MI
The Automated Driving Production Technology Team develops and improves the production technologies, hardware processes, and analytical capabilities that support automated driving systems. We work across engineering, manufacturing, quality, testing, and operations to improve efficiency, scalability, reliability, and performance.
Our team combines expertise in hardware systems, production technology, data science, artificial intelligence, process engineering, and analytics to deliver data-driven improvements to production processes and engineering productivity.
We are hiring an intern to support AI and hardware process efficiency initiatives through data analysis, process optimization, automation, and analytical tool development.
Analyze production, quality, equipment, test, and operational data to identify trends, bottlenecks, variation, and improvement opportunities.
Apply statistical analysis, machine learning, anomaly detection, and other AI techniques to support predictive insights and process optimization.
Develop data pipelines, analytical models, and automated workflows for engineering and production teams.
Evaluate process performance using metrics such as cycle time, throughput, first-pass yield, downtime, capacity utilization, and defect rates.
Support root-cause investigations by connecting process conditions, equipment signals, test results, and quality outcomes.
Measure the impact of process changes and recommend improvements that reduce manual effort, improve throughput, or increase quality.
Create dashboards, reports, and visualizations that support technical and operational decisions.
Document methods, assumptions, findings, and recommendations.
Present results clearly to engineers, technical leaders, and cross-functional stakeholders.
Working toward a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Industrial Engineering, Manufacturing Engineering, Electrical Engineering, Mechanical Engineering, or a related field.
Coursework or project experience in Python, SQL, MATLAB, statistics, data visualization, or machine learning.
Able to work full-time, 40 hours per week.
Experience with Python libraries or tools such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
Familiarity with Power BI, Tableau, time-series analysis, anomaly detection, predictive maintenance, statistical process control, optimization, or design of experiments.
Basic understanding of manufacturing, hardware development, robotics, automated testing, embedded systems, or production operations.
Must be graduating between December 2027 and June 2028
Intent to return to degree program after the completion of the internship.





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