AI-Driven Industrial Engineer – Logistics & Distribution

Airlife; Glendale (AZ); On-site; USD 95,000 - 120,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

401(k) with company match

Paid time off & holidays

Bonus eligibility

Job summary

AirLife in Phoenix/Glendale, AZ is seeking an Industrial Engineer to blend traditional industrial engineering methods with applied AI and analytics to optimize distribution center labor, productivity, and equipment utilization.

You will develop AI-enabled labor standards, dashboards, and predictive models, train operations teams, and support continuous improvement through CI/Lean methods. Occasional travel up to 10% may be needed to support sites.

Qualifications

• Bachelor's degree or higher in Industrial Engineering or equivalent (Supply Chain, Operations, Engineering, Logistics).
• 3+ years in Industrial Engineering.
• 1+ years with AI applications in supply chain or similar.

Responsibilities

• Develop, validate, and maintain time-studied standards using AI-assisted time-and-motion analysis.
• Create a culture of performance management with leader standard work and KPI tracking.
• Provide training to operations teams on labor management systems.
• Create a productivity playbook using CI/Lean principles and technology.
• Develop and deploy AI/ML models to support data-driven decisions (demand and labor forecasting, predictive maintenance).
• Build AI-enabled dashboards and reporting tools for real-time KPI visibility.
• Evaluate layouts, MHE and equipment for productivity improvements using simulation and AI-driven modeling.

Skills

Data-driven decision making

Labor management

Industrial engineering

AI/ML knowledge

statistical analysis

Education

Bachelor's in Industrial Engineering

Tools

Power BI

MS Office

Python

SQL

Job description

AirLife in Phoenix/Glendale, AZ is seeking an Industrial Engineer to blend traditional industrial engineering methods with applied AI and analytics to optimize distribution center labor, productivity, and equipment utilization.

You will develop AI-enabled labor standards, dashboards, and predictive models, train operations teams, and support continuous improvement through CI/Lean methods. Occasional travel up to 10% may be needed to support sites.