Semiconductor Process & Equipment Engineer — Singapore

Micron Technology, Inc.; Singapore; On-site; SGD 78,000 - 123,000; Full time

Job summary

Micron Technology, Inc. is seeking a Process & Equipment Engineer in Singapore to drive process start-up, development, and optimization. You will work on improving yield, quality, and reliability while reducing costs and cycle time.

The role emphasizes solving complex manufacturing issues and applying AI-assisted insights to enhance daily operations. The ideal candidate has a engineering or science degree, strong analytical skills, and a growth mindset.

Qualifications

• 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.
• Knowledge of SPC, Design of Experiment, Engineering Statistical data analysis would be advantageous.
• Ability to apply baseline digital fluency and AI literacy to AI-enabled tools.

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.

Skills

Analytical thinking

Logical thinking

Critical thinking

Effective communication

Collaboration

Leadership

Education

Bachelor's degree in Engineering or Science

Job description

Micron Technology, Inc. is seeking a Process & Equipment Engineer in Singapore to drive process start-up, development, and optimization. You will work on improving yield, quality, and reliability while reducing costs and cycle time.

The role emphasizes solving complex manufacturing issues and applying AI-assisted insights to enhance daily operations. The ideal candidate has a engineering or science degree, strong analytical skills, and a growth mindset.