Micron Technology

ENGINEER - PEE DRY ETCH

Micron Technology
Integrated Device ManufacturingSingapore, SingaporeOnsitePosted 3 months ago

About the role

AI summarised

The Engineer - PEE Dry Etch role at Micron Technology involves supporting process start-up, development, optimization, and troubleshooting for semiconductor manufacturing, particularly in dry etch processes. The position focuses on improving product yield, quality, reliability, and reducing costs through data-driven analysis, root cause investigation, and equipment/material evaluations. The engineer collaborates with cross-functional teams and suppliers to ensure process excellence and compliance with quality and risk management objectives.

IDMOnsiteFront End

Key Responsibilities

  • Establish and improve process condition and technology
  • Upgrade process capability and reduce production cost
  • Establish and modify process management projects
  • Set up process parameters for a variety of semiconductor equipment
  • Evaluation, promotion and planning of new equipment / materials
  • Analyze data and perform root cause analysis to identify and resolve process issues
  • Identify, diagnose and troubleshoot complicated process related problems by applying failure analysis, FMEA, 8D, and SPC methodology
  • Coordinate and execute process/equipment/material evaluations and optimization
  • Implement improvements at process steps/loops
  • Liaise with material suppliers to achieve best in class yield, quality, cost and risk management objectives

Requirements

  • Bachelor’s or advanced degree in Engineering or Science is required
  • Strong analytical, logical, and critical thinking skills
  • Effective communicator, able to collaborate across all levels
  • Growth mindset with a passion for continuous learning
  • Internship or experience in the semiconductor industry is a plus
  • Demonstrated leadership and a track record of impact are highly desirable
  • Interest in and knowledge of the semiconductor industry and Micron is preferred
  • Knowledge of Statistical Process Control (SPC), Design of Experiment, Engineering Statistical data analysis would be advantageous