Summer 2026 Inten - IT MFG Architecture
Western DigitalSan Jose, CAPosted 23 July 2026
Tech Stack
Job Description
This internship sits at the intersection of AI, manufacturing operations, and manufacturing IT. You will apply advanced AI/ML techniques to real-world production challenges across Western Digital's global factories — helping drive digital transformation, improve production efficiency, and accelerate intelligent automation. You will work alongside engineers, data scientists, and IT teams embedded in a fast-paced semiconductor and hard drive manufacturing environment.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Design, build, and deploy AI/ML models and MCP (Model Context Protocol) applications for manufacturing and quality use cases, including defect detection, yield prediction, and process optimization. Work cross-functionally with Production, Manufacturing IT, Equipment, and Process Engineering teams to establish robust data pipelines and end-to-end intelligent solutions. Develop and maintain data visualization dashboards and reporting tools to surface actionable manufacturing insights for operations and IT stakeholders. Implement model-performance monitoring and continuous-improvement loops to ensure stability, explainability, and scalability in production environments. Apply responsible AI practices, including data privacy, access controls, and secure handling of manufacturing and operational data. Contribute to internal tools and frameworks that enhance team productivity and reusability across projects. Participate in Agile development processes, including sprint planning, daily stand-ups, and retrospectives.
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 :
Currently pursuing a BS or MS degree in Computer Science, Industrial Engineering, Operations Research, Data Science, or a related field. Hands-on coursework or project experience applying core AI/ML concepts, including supervised/unsupervised learning, model training, evaluation, and deployment. Proficient in Python; experience with TensorFlow, PyTorch, or Scikit-learn; comfortable with SQL and big-data platforms. Familiarity with data preprocessing, feature engineering, and exploratory data analysis (EDA) techniques. Strong problem-solving skills with the ability to translate ambiguous manufacturing problems into structured, data-driven solutions. Clear written and verbal communication skills; able to present findings to both technical and non-technical audiences.
PREFERRED :
Programming experience in C++, C#, or Java — particularly for manufacturing IT integration or edge/OT system development. Familiarity with LLM/GenAI concepts and tools, including prompt engineering, RAG pipelines, or MCP-based agent frameworks. Exposure to manufacturing domain concepts such as MES (Manufacturing Execution Systems), SECS/GEM, OPC-UA, or OEE metrics. Experience with data visualization tools (e.g., Grafana, Power BI, Tableau) or cloud platforms (Azure, AWS, GCP). Prior internship or research experience in an industrial, semiconductor, or supply chain environment.
 
WD is committed to providing equal opportunities to all applicants and employees and will not discriminate against any applicant or employee based on their race, color, ancestry, religion (including religious dress and grooming standards), sex (including pregnancy, childbirth or related medical conditions, breastfeeding or related medical conditions), gender (including a person’s gender identity, gender expression, and gender-related appearance and behavior, whether or not stereotypically associated with the person’s assigned sex at birth), age, national origin, sexual orientation, medical condition, marital status (including domestic partnership status), physical disability, mental disability, medical condition, genetic information, protected medical and family care leave, Civ ... (truncated, view full listing at source)
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