Intern- Process and Equipment Engineer (Photo)

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Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Location
Singapore

Department
Photolithography Engineering

Project Title
Large-Scale Photolithography Software Stack Integration

Project Description
Photolithography is one of the most software-intensive and technologically advanced manufacturing processes in semiconductor manufacturing. Maintaining world-class performance requires an integrated software ecosystem spanning process control, equipment connectivity, data engineering, automation, visualization, machine learning, and decision-support systems.
As an intern within the Photolithography Engineering team, you will collaborate with process, equipment, data, and manufacturing engineers to design and develop software solutions that transform large-scale manufacturing data into actionable insights and automated engineering workflows.

Project assignments will be tailored to individual strengths, academic background, and learning interests, providing opportunities to contribute across software engineering, data engineering, system integration, analytics, and Artificial Intelligence domains. Where relevant, the project will incorporate AI-Enabled development approaches, Generative AI, Artificial Intelligence, AI Assistants, Agentic AI technologies, and Agentic Solutions to accelerate innovation and engineering problem-solving.

Objective of the Project

• Develop a scalable software solution that addresses a defined photolithography engineering or manufacturing challenge.

• Integrate equipment, manufacturing, and engineering data into reliable digital workflows and software applications.

• Apply software engineering, data analytics, automation, and Artificial Intelligence techniques to improve engineering productivity and decision-making.

• Evaluate AI-Enabled approaches that enhance data accessibility, engineering insights, and workflow efficiency.
   

Opportunities for Full Time Employment

Successful completion of the internship may provide exposure to future graduate employment opportunities, subject to business requirements, position availability, and the applicable selection process.
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Project Scope

• Design and develop desktop, web-based, backend, or data-centric applications for defined photolithography engineering use cases.

• Build software integrations among lithography equipment, databases, Manufacturing Execution Systems, and engineering platforms through appropriate application programming interfaces and data interfaces.

• Develop scalable data pipelines, visualization platforms, monitoring solutions, and workflow automation frameworks for process, equipment, and yield analytics.

• Explore Artificial Intelligence, machine learning, or Agentic AI approaches that enhance engineering analysis and decision-support capabilities.

• Apply modern software engineering practices including version control, testing, deployment, and maintainable software architecture principles.
   

Learning Opportunities

• Gain hands-on experience in software engineering, data engineering, system integration, software testing, and deployment within a semiconductor manufacturing environment.

• Learn how photolithography process, equipment, and manufacturing data are transformed into engineering insights and automated workflows.

• Develop practical experience with Python, Structured Query Language, application programming interfaces, Generative AI tools, AI Assistants, and automation platforms.

• Collaborate with multidisciplinary engineering teams to understand real-world manufacturing challenges and digital transformation initiatives.
   

Deliverables

• A production-quality engineering application, process recipe management solution, equipment connectivity platform, or data analytics system.

• A web-based dashboard, visualization platform, workflow automation framework, or Artificial Intelligence-enabled decision-support solution.

• Relevant source code, testing evidence, technical documentation, and reusable software components.

• A final technical presentation summarizing project architecture, implementation approach, key outcomes, and future recommendations.
   

Impact of the Project

• Strengthen the integration, scalability, and maintainability of the photolithography software ecosystem.

• Improve engineering efficiency, data accessibility, and process visibility through enhanced digital solutions.

• Increase workflow consistency and accelerate data-driven decision-making across engineering functions.

• Establish reusable software components and documented engineering methodologies that can serve as a foundation for future automation, analytics, and AI-Enabled solutions.
   

Skillsets Required

• Working-level experience in at least one programming language such as Python, JavaScript, C#, Go, or shell scripting, together with familiarity with Linux or UNIX environments.

• Familiarity with modern software development practices and tools including Git,SQL,Continuous Integration and Continuous Delivery, containerization technologies, and automated testing frameworks.

• Strong analytical and problem-solving skills with the ability to learn new technologies and collaborate effectively within interdisciplinary engineering teams.

• Familiarity with AI Assistants, Generative AI, Artificial Intelligence, Agentic AI, Large Language Models, or other AI-Enabled development workflows.

• Effective communication skills with the ability to document technical solutions and present project outcomes.
   

Preferred Skillsets

• Experience with web development frameworks, cloud technologies, microservices, or distributed systems.

• Experience with data engineering, data analytics, computer vision, machine learning, Artificial Intelligence, or industrial automation.

• Experience with semiconductor manufacturing systems or relational database platforms such as PostgreSQL or Oracle.
   

Course of Interest
The ideal candidate should be pursuing a degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Electronic Engineering, Data Science, Mathematics, Physics, or a related engineering or science discipline.

Duration of Period
The ideal candidate should be able to commit to a full time internship period of 5 months from Jan to May 2027.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.

To learn more, please visit micron.com/careers

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_sg@micron.com

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.   

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