Silicon Photonics Yield Optimization Engineer

Intel Corporation; Albuquerque (NM); On-site; USD 104,000 - 199,000; Full time

Job summary

Intel Corporation is seeking a Yield Analysis Engineer to analyze semiconductor manufacturing data, identify yield trends, and drive improvements in processes. You will collaborate with cross-functional teams to implement data-driven solutions that enhance product quality and reliability across next‑generation silicon photonics projects.

You will apply statistics and programming tools to evaluate performance, investigate deviations, and develop strategies to minimize defects while supporting

Qualifications

• Bachelor’s degree with 4+ years of semiconductor manufacturing or data analysis experience.
• 2+ years using data analysis or programming tools (Python, R, MATLAB, JMP)
• 2+ years applying statistics and process control methods
• 2+ years handling large datasets and database management

Responsibilities

• Analyze semiconductor manufacturing yield data to identify trends and opportunities.
• Investigate yield issues and deviations, identifying root causes and corrective actions.
• Apply statistical methods to evaluate performance and support data-driven decisions.
• Develop strategies to improve yield and minimize defects in manufacturing processes.
• Generate reports and provide actionable recommendations to improve product quality and reliability.
• Support continuous improvement initiatives to hit yield targets and operational goals.

Skills

Python

R

MATLAB

JMP

Education

Bachelor’s degree in a relevant field

Master’s degree in a relevant field

PhD in a relevant field

Job description

Intel Corporation is seeking a Yield Analysis Engineer to analyze semiconductor manufacturing data, identify yield trends, and drive improvements in processes. You will collaborate with cross-functional teams to implement data-driven solutions that enhance product quality and reliability across next‑generation silicon photonics projects.

You will apply statistics and programming tools to evaluate performance, investigate deviations, and develop strategies to minimize defects while supporting