Intern - AI / Data Science Engineering

You'll be redirected to
the company's application page
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.
Project Title:
Development of Data-Driven Insights and Predictive Models for Semiconductor Manufacturing
Project Description:
This project focuses on applying data analysis, statistical modelling, and machine learning techniques to large semiconductor manufacturing datasets.
The intern will explore how data-driven methods are used to identify patterns, detect anomalies, and develop predictive insights that enhance understanding of process behaviour. The project emphasises structured learning through advanced analytics, data engineering, and visualisation within a high-volume manufacturing environment.
Objective of the project:
To develop analytical models and data-driven insights that improve understanding of manufacturing processes and support informed decision-making.
Project Scope:
- Perform exploratory data analysis on manufacturing datasets to identify patterns, correlations, and trends
- Apply statistical methods such as hypothesis testing and regression analysis to evaluate data
- Develop and evaluate machine learning models for predictive analysis and pattern recognition
- Explore anomaly detection methods to identify deviations in data
- Design basic data workflows for data extraction, preparation, and feature development
- Create data visualisations or dashboards to present analytical insights
- Document approaches, assumptions, and findings in a structured manner
Learning Opportunities:
- Gain hands-on exposure to large-scale semiconductor manufacturing datasets
- Apply machine learning and statistical techniques to real-world engineering problems
- Develop skills in translating analytical results into meaningful insights
- Build understanding of data engineering concepts such as data preparation and feature development
- Strengthen communication skills through presentation of technical findings
- Gain exposure to data-driven decision-making in manufacturing environments
Deliverable:
- End-to-end analytical project including data exploration, modelling, and evaluation
- Machine learning models with documented performance and insights
- Data workflows for preprocessing and feature development
- Data visualisations or analytical reports summarising key findings
- Final presentation and project documentation
Impact of Project:
- Improved understanding of manufacturing data patterns and behaviours
- Contribution to data-driven approaches in process analysis and decision-making
- Development of scalable concepts for analytical modelling and insight generation
Skillsets Required:
- Programming skills in Python for data analysis and modelling
- Basic knowledge of statistics and machine learning concepts
- Familiarity with data querying tools (e.g. SQL)
- Strong analytical thinking and problem-solving skills
- Ability to communicate technical concepts clearly
Course of Interests:
The ideal candidate should be currently pursuing a degree in Electrical and Electronics Engineering, Materials Science, Physics, Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related field.
Duration Period:
Minimum 5 months
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.
Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
Prep Tools
ACE YOUR INTERVIEW IN REAL-TIME
Silent AI Co-Pilot
Real-time interview help
"Why Micron Technology?"
💡 Mention their Semiconductor Manufacturing and your passion for Python
STAND OUT FROM THE CROWD
AI Cover Letter
Tailored for Micron Technology
Dear Micron Technology Hiring Team,
I am excited to apply for the Intern - AI / Data Science Engineering position. With my experience in Python and Statistics...
Continue with AI →
STUCK ON A QUESTION? PRACTICE IT
Practice Any Question
Get instant AI feedback
"How would you design a scalable system for Micron Technology's use case?"