Staff AI/ML Engineer for Yield & Quality Analytics

Micron Technology, Inc.; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

Micron Technology, Inc. is seeking a Staff Engineer in the HIG HBM Product Engineering Advanced Data Analytics team in Singapore. You will lead data-driven initiatives using ML/AI to boost yield, quality, and engineering efficiency across wafer/die-level processes.

You will mentor engineers, drive cross-functional collaboration with Fab, Design, and Quality teams, and advance analytics infrastructure and visualization to enable faster, scalable decision making.

Qualifications

• Bachelor's or Master's degree in Electrical/Electronic Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Data Science, or a related field.
• Strong background in data analytics, statistics, data mining, or data-driven engineering problems.
• Proficiency in Python and data-analysis libraries for large datasets.
• Experience with ML techniques and AI solutions for engineering challenges.

Responsibilities

• Apply advanced analytics, ML, and AI to improve yield, quality, reliability, and engineering efficiency.
• Develop analytics solutions and predictive models for wafer/die-level screening and product disposition.
• Lead cross-functional initiatives and mentor engineers in analytics best practices.
• Build scalable analytics infrastructure, automation, and visualization workflows.
• Collaborate with Fab, HBM Tech Development, Design, System Development, and Quality/Reliability teams.
• Identify innovative methodologies and integrate AI-enabled tooling into daily engineering work.

Skills

Python

Statistical analysis

Machine learning

Data mining

Data visualization

Cross-functional collaboration

Communication

Leadership

Education

Bachelor's or Master's in EE/CS/Data Science

Tools

Power BI

Tableau

Jupyter

Job description

Micron Technology, Inc. is seeking a Staff Engineer in the HIG HBM Product Engineering Advanced Data Analytics team in Singapore. You will lead data-driven initiatives using ML/AI to boost yield, quality, and engineering efficiency across wafer/die-level processes.

You will mentor engineers, drive cross-functional collaboration with Fab, Design, and Quality teams, and advance analytics infrastructure and visualization to enable faster, scalable decision making.