Industrial Engineering Program Manager at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Jan, 26

Salary

0.0

Posted On

18 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Industrial Engineering, Data Science, Manufacturing, Discrete Event Simulation, Lean Manufacturing, Project Management, SQL, Python, Ergonomics, Mathematical Optimization, Computer-Aided Design, Factory Efficiency, Process Improvement, Simulation, Heuristics, Control Systems

Industry

Computers and Electronics Manufacturing

Description

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. We believe that it’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. In this highly impactful role, you will be leading efforts to make things better, may it be products, processes or systems. You will bring your passion and thirst for excellence in the fields of digital manufacturing and factory efficiency to drive improvements and new technologies at our manufacturing facilities to ensure optimum use of resources. DESCRIPTION - Modeling and evaluating discrete process simulations - Designing the layout of the plant using computer-aided design/manufacturing (CAD/CAM) software to build 3D models - Designing, developing and installing plant control systems - Liaising with designers, researchers and engineering consultants - Investigating process ergonomics and coming up with solutions for any perceived issues - Factory Efficiency and Metrics - Calculating production costs and metrics that include time, labor, space, equipment and overhead - Maintaining product process flow, layout and parameters - Implementing lean principles to various factory related processes - Deciding on the effective use of resources, e.g. raw materials, equipment and labor - Factory benchmarking for best in class metrics - Design, develop, and apply engineering, mathematical models, simulation and optimization models to drive solutions to complex manufacturing operations problems / challenges. - Work on building heuristics to analyze factory collected data and define methodologies for answering key manufacturing questions. - Visiting CMs and other production sites to lead IE discussions, evaluate onsite processes and provide improvement direction - Managing development and implementation of projects at contract manufacturers (CMs) - Ability to travel internationally 20% MINIMUM QUALIFICATIONS 5+ years of experience in industrial engineering, data science, or manufacturing Bachelor's degree in industrial engineering, operations research or engineering discipline PREFERRED QUALIFICATIONS Prefer a Master's degree in industrial engineering, operations research or engineering discipline Ability to run discrete event simulation in FlexSIM and PlantSIM Exposure to ergonomic validations using Siemens Jack or Process Simulate Human Experience with Design for Assembly/Manufacturing Experience with Lean Manufacturing Exposure to predetermined time standards such as MODAPTS, MOST or MTM Experience in Operations Research/Mathematical optimization Familiar with the fundamentals of machine learning and deep learning. Good interpersonal, collaboration, presentation and communication skills Strong project management skills and the ability to work to tight project deadlines Experience with SQL and/or Python

Responsibilities

You will lead efforts to improve products, processes, and systems at manufacturing facilities. This includes modeling discrete process simulations, designing plant layouts, and implementing lean principles.