Intern - NAND Device Engineering AI

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 16,740 - 33,480; Full time

Job summary

1100 Micron SemiAsiaOP Pte Ltd in Singapore is offering an internship for an AI / Data Science Intern. In this role, you will design AI automation workflows and develop decision-support tools to enhance device characterization processes in NAND technologies.

Applicants should be pursuing a relevant degree and possess strong Python skills, with a sound understanding of machine learning. The internship aims to make a significant impact by helping teams work more efficiently.

Qualifications

• Currently pursuing a relevant degree.
• Strong proficiency in Python required.
• Experience in ML or AI applications preferred.

Responsibilities

• Design and develop AI-powered automation workflows.
• Build intelligent decision-support tools.
• Create automated data pipelines.

Skills

Python

Machine Learning

Data Analysis

Automation Workflows

Education

Bachelor's / Master's / Ph.D in Computer Science or related field

Tools

TensorFlow

PyTorch

SQL

Tableau

Power BI

Job description

Role Overview

As an AI / Data Science Intern in the NAND Device Engineering group, you will apply artificial intelligence and data science techniques to accelerate and automate device characterization, enable autonomous data analysis and decision-making, improve task and project management, and increase efficiency across all facets of development in advanced 3D NAND technologies. You will design and build intelligent automation workflows, AI-assisted decision‑support systems, and scalable data pipelines that empower engineering teams to work faster and smarter — from routine characterization tasks to strategic project execution.

Key Responsibilities

• Design and develop AI‑powered automation workflows for electrical characterization of 3D NAND memory cells, including automated data extraction, analysis, reporting, and anomaly flagging across program, read, erase, reliability, and variability datasets.
• Build intelligent decision‑support tools that synthesize large‑scale device data into prioritized, actionable recommendations — enabling faster engineering decisions on device optimization, design‑of‑experiment planning, and risk assessment.
• Develop AI‑driven task and project management solutions that automate tracking, prioritization, status reporting, and follow‑up across device engineering projects and cross‑functional workstreams.
• Apply machine learning techniques (classification, regression, clustering, NLP, agentic AI) to automate pattern recognition, trend identification, and root‑cause analysis in device performance datasets.
• Create automated data pipelines for data extraction, cleaning, feature engineering, and integration across multiple characterization and metrology data sources.
• Build interactive visualizations, dashboards, and auto‑generated summary reports that communicate device insights to technical and non‑technical audiences with minimal manual effort.
• Explore and implement LLM‑based and agentic AI approaches for automating routine engineering workflows such as data interpretation, report generation, meeting summarization, and knowledge retrieval.
• Work independently with a high level of self‑motivation, time management, and prioritization skills.
• Deliver a complete intern project package, including code/notebooks, automation tools, documentation, and presentation‑ready summaries.

Education and Experience

Currently pursuing a Bachelor's degree / Master's degree / Ph.D in Computer Science, Data Science, Artificial Intelligence, Statistics, Electrical Engineering, Physics, Mathematics, or a related field, and available preferably for a semester‑long internship.

• Strong proficiency in Python and experience building end‑to‑end data analysis or automation workflows is required.
• Demonstrated experience or coursework in machine learning, deep learning, or AI applications (scikit‑learn, TensorFlow, PyTorch, LangChain, or similar frameworks) is required.
• Experience with automation and workflow orchestration (e.g., scripting pipelines, API integrations, Power Automate, Airflow, or similar tools) is highly preferred.
• Familiarity with LLMs, NLP, or agentic AI frameworks for building intelligent assistants or automated workflows is a strong plus.
• Experience with SQL, data visualization tools (Tableau, Power BI, Streamlit), or dashboard development is a plus.
• Exposure to semiconductor device physics, NAND flash memory, or electrical characterization is a plus.
• Experience with cloud platforms (Azure, AWS, GCP) or big data tools (Spark, BigQuery) is a bonus.

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.