Yield Excellence Engineer — Advanced Semiconductor Fab

TSMC; Arizona; On-site; USD 110,000 - 130,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

TSMC Arizona invites applications for a Yield Enhancement Engineer in Phoenix, AZ. You will contribute to defect reduction, yield improvement, and inspection methodology excellence in a fast-paced, 24/7 semiconductor manufacturing environment.

The role requires a Bachelor's or higher in Electrical Engineering or Materials Science, hands-on defect metrology tool experience, strong collaboration across functions, and proven ownership in solving complex process issues.

Qualifications

• Bachelor's or higher degree in Electrical Engineering, Material Science.
• Experience in bright field, darkfield and Ebeam defect metrology tool usage.
• Experience in inline usage of above tools to monitor/detect integrated and process tool shifts in a high volume 24/7 advance manufacturing fab.
• Passion for collaboration with process integration equipment in driving improvements.
• Good communication and interpersonal skills.
• Able to work on cross-functional and geographically dispersed teams with diverse backgrounds.
• Must take ownership for solving issues and ensures escalations take place.
• A team player that can multitask and thrive in a very dynamic and fast-paced environment.

Responsibilities

• Defect reduction and yield improvement responsibilities.
• Inspection methodology excellence.

Skills

Defect metrology

Cross-functional

Communication

Ownership

Education

Bachelor's or higher degree in Electrical Engineering, Material Science

Job description

TSMC Arizona invites applications for a Yield Enhancement Engineer in Phoenix, AZ. You will contribute to defect reduction, yield improvement, and inspection methodology excellence in a fast-paced, 24/7 semiconductor manufacturing environment.

The role requires a Bachelor's or higher in Electrical Engineering or Materials Science, hands-on defect metrology tool experience, strong collaboration across functions, and proven ownership in solving complex process issues.