Industrial Engineering Intern: AI & Process Optimization

UPS; Dallas (TX); Presencial; USD 28.000 - 39.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

401(k) retirement program

Personal time

Discounted Employee Stock Purchase

Descripción de la vacante

UPS is offering an Industrial Engineering Internship in Dallas, TX for students or recent graduates. You will participate in targeted projects, observe operations, collect data, and present findings to the Industrial Engineering staff.

Responsibilities include work measurement, cost‑benefit analyses, process improvements, and operational planning, with opportunities to apply AI, automation, and data analytics to improve efficiency and support engineering initiatives.

Formación

• Knowledge of industrial engineering or related discipline required.
• Strong statistical analysis skills.
• Effective research and communication abilities.
• Enthusiasm, creativity and dedication to results.
• Ability to work both independently and in teams.
• Excellent written and verbal communication across units.

Responsabilidades

• Work measurement in MSD and related data collection tasks.
• Conduct cost‑benefit analyses and inform decisions.
• Perform process improvement analyses and recommend changes.
• Support operational planning and scheduling activities.
• Explore and apply AI, automation, and data analytics to boost efficiency.

Conocimientos

Industrial Engineering knowledge

Statistical analysis

Research and communication

Teamwork

Interpersonal skills

Written and oral communication

Educación

College/university student (enrolled)

Descripción del empleo

UPS is offering an Industrial Engineering Internship in Dallas, TX for students or recent graduates. You will participate in targeted projects, observe operations, collect data, and present findings to the Industrial Engineering staff.

Responsibilities include work measurement, cost‑benefit analyses, process improvements, and operational planning, with opportunities to apply AI, automation, and data analytics to improve efficiency and support engineering initiatives.