Lean AI, Industrial Engineer

AirLife•Glendale, AZ

11d

About The Position

The Industrial Engineer will provide engineering and project support to Distribution Centers by combining traditional industrial engineering methods with applied AI and advanced analytics. Drive labor optimization by improving productivity through engineered labor standards, AI-driven forecasting and predictive models, KPI’s, automation technology, and continuous improvement initiatives supports day-to-day distribution center performance through data analytics, machine learning models, labor management analysis, and visual management tools. This role focuses on using statistical analysis, AI/ML techniques, and operational data to improve labor efficiency, productivity, predictive maintenance, and workflow visibility within the distribution center while supporting continuous improvement initiatives.

Requirements

3+ years of work experience in Industrial Engineering.
1+years of work experience with AI application in supply chain or similar
Bachelor's degree or higher in Industrial Engineering or equivalent degree such as Supply Chain, Operations, Engineering, Logistics is required.
Distribution center/logistics concepts – understanding of warehousing best practices.
Ability to drive decision making through data and relevant business metrics.
Ability to resolve problems in a timely manner with little or no supervision.
Excellent verbal and written communication skills.
Strong interpersonal skills and ability to work cross functionally.
Must be able to utilize problem solving techniques to identify root causes of failures and solutions to meet targets.
Strong business planning and analytical skills including market intelligence, metrics, financial and analysis.
Ability to manage project portfolio of varying priorities and impact value.
Strong computer skills including Power B.I, MS Office
Proficiency with Python, SQL, or similar tools for data analysis and predictive modeling a plus.

Nice To Haves

MSD/MOST experience preferred
Experience applying machine learning or statistical modeling to operational problems (e.g., demand forecasting, labor forecasting, predictive maintenance) preferred.
Familiarity with simulation or discrete-event modeling tools (e.g., Arena, FlexSim, AnyLogic) a plus.
Experience in developing engineered labor standards.
Continuous improvement experience and knowledge of CI methodologies preferred.
Experience within the distribution/warehouse/logistics industry preferred.
Proficient in RF Scanning and Warehouse Management Systems preferred.
Experience in semi and fully automated material handling systems a plus.

Responsibilities

Develop, validate, and maintain time-studied standards for overall operation and for each function, leveraging AI-assisted time-and-motion analysis and predictive labor models where applicable
Create a culture of performance management through leader standard work, productivity meetings and KPI
Provide training to operations teams on labor management and associated systems
Create a playbook of productivity improvements using CI/Lean principles and technology
Develop and deploy AI/ML-based models (e.g., demand and labor forecasting, predictive maintenance) to support proactive, data-driven decision-making
Build and maintain automated, AI-enabled dashboards and reporting tools to increase real-time visibility into labor, throughput, and equipment KPIs
Write all SOP’s for operations and ensure employee training program in place
Evaluate and make recommendations on layouts, MHE and other equipment to optimize productivity, using simulation and AI-driven scenario modeling to validate changes before implementation.
Uphold and embody AirLife’s values in all aspects of work.
Demonstrate accuracy and thoroughness in daily work; look for ways to improve and promote quality & safety.
Inspire the trust of others; treat people with respect and dignity and embrace the value of diversity.
Use time efficiently; perform job accurately, thoroughly, and conserve Company resources to improve profits.
Contribute to building and maintaining a positive team environment.
Assure all policies and guidelines are implemented and followed.