INTERNSHIP DETAILS

Intern - Automation Development Engineer (Studying Master's Degree)

CompanyWestern Digital
LocationPhra Nakhon Si Ayutthaya City Municipality
Work ModeOn Site
PostedJuly 10, 2026
Internship Information
Core Responsibilities
The intern will design and execute analytics or machine learning projects to improve manufacturing processes. Key tasks include building data pipelines, developing predictive models, and presenting findings to engineering leadership.
Internship Type
intern
Company Size
22796
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
For more than 55 years, WD has built the storage infrastructure that powers the world’s data. Now, as WD, we’re driving certainty for the AI-driven data economy—delivering the scale, reliability, and economics required to turn data into intelligence.
About the Role

Company Description

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 Description

ESSENTIAL DUTIES AND RESPONSIBILITIES:

The Data Analytics / Computer Science Intern (Master's Level) will join Western Digital's Head Backend Business Unit for a structured 3-6 month internship at the Thailand site (THO). This graduate-level role is designed for students with advanced analytics or AI/ML capabilities who can contribute independently to meaningful data initiatives within a precision manufacturing environment. 

The intern will work on substantive analytics projects -- including predictive modeling, process intelligence, or automation initiatives -- under the guidance of senior engineering staff. Strong performers will be considered for conversion to the ECT - Data Analytics (Master's) track under the BEST Program. 

High-performing interns will be considered for conversion to the ECT - under the BEST Program. 

Key responsibilities include: 

  • Designing and executing an analytics or ML project with defined scope and measurable deliverables 
  • Building or enhancing data pipelines, models, or dashboards used by engineering teams 
  • Applying advanced statistical or machine learning techniques to manufacturing process data
  • Documenting methodology and presenting results to engineering leadership 
  • Collaborating with process engineers to ensure outputs are operationally relevant 
  • Participating in structured internship assessments and IDP-lite development conversations

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.

Qualifications

REQUIRED: 

  • Currently pursuing a Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering with advanced analytics/AI specialization, or equivalent experience
  • Completed a Bachelor's degree in a technical field 
  • Advanced proficiency in Python and/or R; working knowledge of SQL 
  • Active thesis or project in ML, data science, or applied analytics 
  • Available for 3-6 months structured internship 

PREFERRED: 

  • Research or thesis involving machine learning, predictive modeling, or process analytics 
  • Familiarity with cloud platforms (AWS, Azure, GCP) or big data tools 
  • Experience with time-series data, anomaly detection, or sensor analytics 
  • Publication, competition recognition, or open-source contribution in data/AI 
  • Exposure to manufacturing or industrial data environments 

SKILLS: 

  • Advanced Python/R with software engineering best practices 
  • Machine learning model development and validation 
  • Statistical analysis and experimental design 
  • Strong analytical communication - ability to present complex findings clearly 
  • Independent project management with structured deliverables 
  • High intellectual curiosity and research discipline
  • Strong written and verbal English communication 

Additional Information

#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  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 .

  • Job Type (exemption status): Exempt position - Please see related compensation & benefits details below
  • Business Function: Engineering Support
  • Work Location: BangPa-In Building 2--LOC_WDT_TH1412
  • Key Skills
    PythonRSQLMachine LearningStatistical AnalysisData Pipeline ConstructionPredictive ModelingExperimental DesignProject ManagementAnalytical CommunicationSoftware Engineering Best PracticesModel Validation
    Categories
    Data & AnalyticsEngineeringTechnologyManufacturingSoftware