
Semiconductor Yield / Defect Engineer (Wafer Fab, SEM Defect Review)
micro1
At a glance
Semiconductor Yield / Defect Engineer (Wafer Fab, SEM Defect Review) is a remote engineering opening at micro1. The posting places it in Remote. The post date on the listing is 8 Nov 2026. No deadline is filled in on the listing. The notes below are written by Akazi. The advertisement under them is the employer's own text.
- Company
- micro1
- Job type
- Engineering · Remote
- Location
- Remote
- Deadline
- Deadline not listed
- Date posted
- 8 Nov 2026
How to apply
- Semiconductor Yield / Defect Engineer (Wafer Fab, SEM Defect Review) is listed here so you can find it. micro1 takes the application. Akazi does not.
- Use Apply. It opens the employer's own site. Finish every step there, including an account if they ask for one.
- No deadline is stored in the listing fields. Read the advert in case the date is only written in the text, and apply while it is still open.
- It is remote (Remote). Say that you are based in Rwanda, which hours you can overlap with the team, and which languages you work in.
- Shape your CV around this engineering role and put the experience they ask for near the top. Name Kinyarwanda, English, or French only at the level you can actually work in.
- Do not pay a fee, buy a starter kit, or share a mobile-money PIN. A real application to micro1 will not ask you to pay in order to be hired.
Writing a CV for Rwanda · Preparing for interviews · Remote work from Rwanda
Apply(opens in a new tab)Employer advertisement
The text below is the public posting from micro1. Akazi did not write it.
Role Title : Semiconductor Yield / Defect Engineer (Wafer Fab, SEM Defect Review)
Role Type : Contractor
Location : Remote
micro1 is engaging Semiconductor Yield / Defect Engineers (Wafer Fab, SEM Defect Review) to support a customer engagement focused on advancing semiconductor manufacturing analytics. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is ideal for yield, defect, or process integration experts with direct hands-on experience in wafer fab production environments, especially those familiar with facilities operating their own sort floors. Retired or former fab engineers are highly encouraged to participate and share their invaluable experience.
Scope of Work
Conduct SEM (Scanning Electron Microscope) defect review and accurate classification of defects observed in wafer fabrication processes. Interpret and analyze yield loss mechanisms, correlating defect patterns with process-related issues. Evaluate excursion events and make informed lot-hold or release recommendations based on empirical evidence and industry best practices. Review, interpret, and annotate wafer sort and test floor data, including bin maps and parametric datasets. Identify defect paretos and contribute to source attribution analysis to trace root causes. Document observations, communicate technical findings, and provide actionable feedback in clear, concise written and verbal formats for integration into AI learning modules.
Preferred Qualifications
Extensive hands-on experience in wafer fab environments, with a focus on SEM-based defect review and yield analysis. Demonstrated expertise in production fabs with integrated sort/test floors; experience limited to research cleanrooms does not qualify. Proficiency with defect classification methodologies, excursion management, and yield improvement strategies. Strong ability to analyze wafer sort/bin data and interpret test floor metrics to inform defect and yield investigations. Exceptional written and verbal communication skills, able to explain complex technical concepts to diverse audiences. Background in process integration or defect/yield engineering at major semiconductor manufacturing facilities. Experience as a retired or former fab engineer considered a valuable asset.
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