Intern - SSD Assembly Process & Equipment Engineering

Micron Technology; Singapore; On-site; SGD 15,000 - 19,000; Full time

Job summary

Micron Technology, Inc. invites a full-time 5-month internship in Singapore to characterize SSD depanel processes. You will run DOE studies, analyze data, and collaborate with equipment engineers to optimize process capability. The role explores AI-enabled analytics to accelerate insight generation and reporting.

You will gain hands-on experience in semiconductor process engineering, data visualization, and cross-functional teamwork, with opportunities for future roles.

Qualifications

• Pursuing a degree in Mechanical/Mechatronics/Electrical/Manufacturing Engineering or related field.
• Strong analytical and problem-solving skills with teamwork ability.
• Familiarity with DOE, process characterization, and optimization methods.

Responsibilities

• Conduct DOE studies for SSD depanel operations and analyze results.
• Identify critical inputs, variation sources, and optimization opportunities.
• Collaborate with cross-functional teams to validate findings and implement improvements.
• Develop data visualization and reporting tools to communicate insights.

Skills

DOE design

Statistical analysis

Python

JMP

Minitab

SQL

Power BI

AI/Generative AI

Data visualization

Team collaboration

Education

Mechanical Eng or related

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.

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 [e-mail]

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.