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.
Job DescriptionESSENTIAL DUTIES AND 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
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.
QualificationsREQUIRED:
We warmly welcome fresh graduates of a Master's degree, and Early Career Talent with 0–2 years of experience are encouraged to apply.
- 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
PREFERRED:
- 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
SKILLS:
- 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
#LI-SB1
WD thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.
WD is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [email protected] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Notice To Candidates: Please be aware that WD and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to WD Ethics Helpline or email [email protected].
Skills Required
- Master's degree (pursuing or recently completed) in Manufacturing, Industrial, or Mechanical Engineering or equivalent experience
- Fundamental understanding of manufacturing processes, production flow, and capacity concepts
- Basic knowledge of productivity improvement and industrial engineering principles (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 manufacturing
- Proficiency in Microsoft Excel and PowerPoint
- Data analysis and structured problem‑solving ability
- Teamwork, collaboration with Manufacturing Engineering and Operations, and clear communication/presentation skills
- 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 projects
- Coursework or project experience in Lean Manufacturing, Six Sigma, or Continuous Improvement
- Experience using data analysis tools (dashboards, basic simulations) for capacity or productivity analysis
- Academic/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
Western Digital Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Western Digital and has not been reviewed or approved by Western Digital.
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Strong & Reliable Incentives — Strong & Reliable Incentives: Incentive structures in variable‑pay roles are portrayed as well‑designed, and annual or quarterly bonuses are commonly part of total compensation.
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Healthcare Strength — Healthcare Strength: Company materials highlight comprehensive medical, dental, vision, and mental‑health resources, complemented by options like HSA/FSA and disability coverage.
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Parental & Family Support — Parental & Family Support: Caregiving support across life stages and children’s behavioral health resources are featured, with programs such as Bright Horizons referenced for U.S. employees.
Western Digital Insights
What We Do
At Western Digital we create data storage solutions that power the technology of today and inspire the innovations of tomorrow.








