Intern - SSD Assembly Process & Equipment Engineering

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 8,900 - 18,000; Full time

Job summary

Micron Technology, Inc. in Singapore invites an intern to join the SSD depanel process engineering team for a 5-month period from Jan to May 2027.

You will conduct DOE studies, analyze process data, and use AI-enabled analytics to improve manufacturing reliability and product quality.

This hands-on project offers exposure to data visualization, cross-functional collaboration, and opportunities for potential full-time employment.

Qualifications

• Foundational knowledge of process engineering, statistics, or manufacturing systems.
• Interest in DOE, process characterization, and optimization methodologies.
• Exposure to AI-enabled analytical tools is advantageous.

Responsibilities

• Characterize key factors influencing SSD depanel performance.
• Conduct DOE studies and analyze process data to identify variation sources.
• Develop AI-enabled analytics to automate analysis and reporting.
• Collaborate with cross-functional engineering and equipment teams.

Skills

Process engineering

Statistics

Manufacturing systems

DOE

Data analysis

Python

JMP

Minitab

SQL

Power BI

AI/Generative AI

Teamwork

Education

Degree in Mechanical Engineering

Degree in Mechatronics Engineering

Degree in Electrical Engineering

Degree in Manufacturing Engineering

Degree in Industrial Engineering

Degree in Materials Engineering

Tools

Python

JMP

Minitab

SQL

Power BI

Job description

Our vision is to transform how the world uses information to enrich life for all. 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 SSD Assembly Process & Equipment Engineering Project Title AI-Enabled SSD Depanel Process Characterization and Optimization

Project Description

This internship project focuses on characterizing process variations in SSD depanel operations within a high-volume manufacturing environment. The project aims to deepen understanding of the interactions between process parameters, equipment performance, and product quality outcomes. The intern will undertake a structured engineering project involving Design of Experiments (DOE), statistical analysis, process characterization, and data-driven optimization techniques. In addition, the intern will explore AI-Enabled approaches to improve engineering productivity, automate data interpretation, and accelerate insight generation from process characterization activities. The project provides an opportunity to gain hands-on experience in process engineering, equipment operations, and advanced manufacturing technologies within the semiconductor industry.

Objective of the Project

Characterize key process variables affecting SSD depanel performance and product quality. Establish a robust operating window that satisfies mechanical and reliability requirements while minimizing board damage and cosmetic defects. Apply statistical and engineering methodologies to optimize process capability and stability. Explore AI-Enabled analytics techniques to accelerate engineering analysis and decision-making.

Opportunities for Full Time Employment

Interns demonstrating strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time opportunities, subject to business needs and evaluation outcomes.

Project Scope

Conduct process characterization studies for SSD depanel operations using statistical Design of Experiments (DOE) methodologies. Analyze process and equipment data to identify critical process inputs, sources of variation, and optimization opportunities. Collaborate with cross-functional engineering and equipment stakeholders to validate findings and evaluate improvement opportunities. Develop data visualization and reporting tools to communicate process insights and recommendations. Evaluate the use of Artificial Intelligence, Generative AI, or AI Assistant tools for automated analysis, report generation, and engineering knowledge capture.

Learning Opportunities

Gain hands-on experience in process characterization, DOE execution, and manufacturing process optimization. Develop practical knowledge of SSD assembly processes, equipment engineering, and semiconductor manufacturing operations. Learn advanced data analysis and visualization techniques for engineering applications. Gain exposure to AI-Enabled engineering workflows, including Generative AI applications for technical reporting and insight generation. Strengthen project management, technical communication, and cross-functional collaboration skills.

Deliverables

Comprehensive characterization study identifying key factors influencing SSD depanel performance. Established operating window with supporting statistical analysis and engineering rationale. AI-Enabled analysis or proof-of-concept demonstrating automated insight generation, anomaly detection, or engineering reporting. Final project report and presentation summarizing methodology, findings, recommendations, and potential future improvement opportunities.

Impact of the Project

Improve understanding of process variation and equipment interactions within SSD depanel operations. Support development of a more robust and stable manufacturing process. Enable data-driven decision-making through statistical analysis and process characterization. Demonstrate opportunities for AI-Enabled solutions to improve engineering productivity and analysis efficiency.

Skillsets Required

Foundational knowledge of process engineering, statistics, or manufacturing systems. Interest in Design of Experiments (DOE), process characterization, and process optimization methodologies. Familiarity with data analysis tools such as Python, JMP, Minitab, SQL, Power BI, or equivalent platforms. Exposure to Artificial Intelligence, Generative AI, or AI-Enabled analytical tools is advantageous. Strong analytical thinking, problem-solving capability, communication skills, and ability to work effectively in a team environment.

Course of Interest

The ideal candidate should be pursuing a Degree in Mechanical Engineering, Mechatronics Engineering, Electrical Engineering, Manufacturing Engineering, Industrial Engineering, Materials Engineering, or a related 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.

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.