Industrial Engineer - Semiconductor

Leading Global Talent Acquisition for R&D, Eyepiece, Hardware, Manufacturing, Supply Chain & Internships at Magic Leap

A new paradigm of computing

Magic Leap is a pioneer in Augmented Reality (AR) optics, display systems, platforms, devices services, prototyping and manufacturing capabilities. We are known for our unmatched optics stack and have developed ultra-lightweight wave guides and display systems that advance what is possible in AR. With more than a decade of experience in AR innovation, we have made groundbreaking advancements in text legibility, color fidelity and rich digital content visuals while continually expanding the field of view to create engaging, immersive AR experiences.

Magic Leap could be your place if you want to be part of a united team where everyone is empowered and trusted to make an impact. At Magic Leap, you can explore innovative solutions and use your talents to solve real-world problems. Working alongside industry experts, you can grow your skills while helping make our technology available to millions of people as a partner in the mixed reality (XR) ecosystem.

We know that successful change and progress accelerates diverse perspectives. As we shape our future, everyone's voice matters. Together, we can reimagine the world of work and, with our bold partners, make the impossible possible.

We are seeking a highly skilled Staff Industrial Engineer with a strong background in semiconductor factory automation and advanced manufacturing systems. This role is ideal for an experienced engineer who can bridge the gap between equipment, process, and data, transforming complex manufacturing operations into highly efficient, automated production environments.

The ideal candidate has a proven track record in semiconductor fabrication, as well as proficiency in Automated Material Handling Systems (AMHS), including Overhead Hoist Vehicles (OHV) and Automated Guided Vehicles (AGV), and experience with simulation and layout tools such as Flex Sim, AutoCAD, or equivalent.

This role is based onsite at our Plantation, FL office. Relocation assistance may be provided for qualified candidates. The position may require up to 25% travel, both domestically and internationally, to support cross-site collaboration, vendor coordination, and project implementation.

• Optimize equipment utilization, WIP flow, and capacity planning.
• Partner with R&D, Quality, and Production teams to transition new processes into high-volume manufacturing.
• Facilitate Kaizen workshops, standard work documentation (SOPs, work instructions), and GMP compliance.
• Mentor engineers and technicians in process troubleshooting, preventive maintenance, and yield optimization.
• Perform time studies, value stream mapping, and OEE analysis to identify and eliminate waste.
• Engage directly with equipment vendors and contractors to resolve complex manufacturing issues.
• Ability to summarize complex information into executive-friendly presentations.

• B.S. in Industrial Engineering.
• 7+ years of experience in semiconductor or optics manufacturing, including automation projects.
• Proven experience with AMHS / OHV / AGV systems or other semiconductor automation technologies.
• Proficiency in AutoCAD for layout and space optimization.
• Proficiency in Flex Sim, Siemens Plant Simulation, or similar discrete event simulation tools.
• Advanced knowledge of SPC, MSA, CPK, OEE, and DOE methodologies.
• Six Sigma Green Belt or higher certification.
• Skilled in data analysis tools such as JMP, Minitab, or Python for process modeling.
• Excellent communication, presentation, and cross-functional leadership skills.
• Hands‑on cleanroom experience in semiconductor or optics manufacturing.
• Familiarity with wet cleans, lithography, etching or vacuum process tools.
• Experience in designing automation layouts and data-driven process control loops.
• Management of an industrial engineering team.

• Strong analytical problem solver with systems-level thinking.
• Excellent project management and multitasking skills in fast-paced environments.
• Deep understanding of lean manufacturing principles and statistical thinking.
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