Senior Engineer, Manufacturing Engineering

WD is building the infrastructure behind the AI-driven data economy.

As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time. That’s where we come in.

We combine deep engineering expertise with global-scale manufacturing to deliver the storage systems that make AI possible, powering hyperscale data centers, cloud platforms, and enterprise infrastructure worldwide.

This isn’t theoretical work. It’s real systems, at real scale, people solving some of the hardest challenges in technology today.

We’re looking for people who want to build, solve, and operate at that level.

Join us and let’s shape the future of data.

ESSENTIAL DUTIES AND RESPONSIBILITIES

This position is part of our Early Career program at WD. Our Early Career program is designed to support individuals beginning their professional career by providing the foundational training through a structured onboarding, mentorship, and development curriculum.

REQUIRED

We warmly welcome fresh graduates of a Master's degree, and Early Career Talent with 0–2 years of experience are encouraged to apply.

Responsibilities

Support Manufacturing Engineering team in resolving production capacity‑related issues; Assist in productivity and DGR improvement activities through data analysis and process studies; Support capacity line setup, line conversion, scheduling, and production ramp‑up activities; Participate in day‑to‑day production capacity and output gap analysis and issue resolution; Support OEE / TEEP data collection, analysis, and improvement initiatives; Assist in coordinating manufacturing cost improvement projects; Support capital budget requests, purchase requisitions, and on‑time equipment ordering tracking; Develop and improve team processes by creating or supporting digital applications using AI, Industry 4.0 (4IR), and other digital technologies to improve efficiency

Requirements

Currently pursuing or recently completed Master's degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering , or equivalent experience; Fundamental understanding of manufacturing processes, production flow, and capacity concepts gained through coursework or academic projects; Basic knowledge of productivity improvement and industrial engineering principles (e.g., line balancing, cycle time, throughput); Introductory understanding of OEE / equipment efficiency metrics; Ability to support production capacity and output gap analysis under guidance; Basic awareness of manufacturing cost concepts and willingness to participate in cost improvement activities; Willingness to learn and assist with capital equipment justification, purchase requests, and order tracking; Strong interest in applying AI, Industry 4.0, and digital technologies to improve manufacturing efficiency; Fundamental manufacturing engineering and process analysis skills; Basic capacity planning and productivity improvement skills; Data analysis and structured problem‑solving ability; Ability to support OEE/TEEP improvement activities; Strong learning agility and willingness to work hands‑on in a production environment; Teamwork and collaboration with Manufacturing Engineering and Operations teams; Clear communication and basic technical presentation skills; Proficiency in Microsoft Excel and PowerPoint; Curiosity and an innovative mindset toward AI, 4IR, and digital application development

Nice to have

Internship, co‑op, or project experience in a manufacturing or production environment; Exposure to line setup, line conversion, or production ramp‑up through internships or university projects; Coursework or project experience in Lean Manufacturing, Six Sigma, or Continuous Improvement; Experience using data analysis tools (Excel, dashboards, basic simulations) for capacity or productivity analysis; Academic or project exposure to AI, data analytics, automation, smart manufacturing, or digital factory concepts; Familiarity with manufacturing KPIs such as output, yield, OEE, or cycle time