AI & MES Intern: Digital Manufacturing Data (Summer 2027)

Nissan Motor Iberica SA; Smyrna (TN); Hybrid; USD 25,000 - 30,000; Full time

Job summary

Nissan Motor Iberica SA is seeking a Manufacturing Digital Data Intern for Summer 2027 in Smyrna, TN. The role focuses on MES, data analytics, and AI-enabled solutions to enhance production visibility and decision-making in a world-class manufacturing setting.

You will work on developing digital tools, monitoring production operations, and collaborating with cross-functional teams to identify efficiency improvements.

Qualifications

• Must be currently enrolled in an undergraduate or graduate degree program in Computer Science, Information Systems, Software Engineering, Data Analytics, or a related field.
• Junior or Senior year at the start of the upcoming academic term.
• GPA of 3.0 or above with official/unofficial transcript provided during application.
• Ability to work onsite at Smyrna, TN.

Responsibilities

• Support the development and enhancement of manufacturing floor systems used to monitor and optimize production operations.
• Assist with MES projects that improve process efficiency and data visibility.
• Design, develop, and maintain HMI screens for manufacturing applications.
• Collaborate with engineering and production teams to identify digital-technology driven improvements.
• Support data and AI initiatives that drive operational excellence and manufacturing performance.

Skills

VB Script

C#

PowerShell

Education

Undergraduate or graduate degree in Computer Science, Information Systems, Software Engineering, Data Analytics, or related field

Job description

Nissan Motor Iberica SA is seeking a Manufacturing Digital Data Intern for Summer 2027 in Smyrna, TN. The role focuses on MES, data analytics, and AI-enabled solutions to enhance production visibility and decision-making in a world-class manufacturing setting.

You will work on developing digital tools, monitoring production operations, and collaborating with cross-functional teams to identify efficiency improvements.