Yield Optimization Engineer — Data‑Driven Semiconductors

Intel; Hillsboro (OR); Hybrid; USD 133,800 - 255,200; Full time

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Job summary

Intel in Hillsboro, Oregon is seeking an Experienced Hire to join our semiconductor yield analytics team. You will apply statistics, ML, and DOE to drive process innovation, reduce defects, and improve manufacturability across advanced fabrication steps.

You will collaborate with process integration, defect engineering, and design teams to identify root causes, build yield models, and develop tools that convert manufacturing data into actionable improvements for next-generation devices.

Qualifications

• Bachelor's/Master's/PhD in engineering or physical sciences with related semiconductor experience.
• Experience with data analysis, machine learning, SPC, and DOE.
• Experience in defect engineering or yield improvement preferred.

Responsibilities

• Perform statistical analysis to develop process roadmaps and yield milestones.
• Consolidate data to identify defect modes and build yield models.
• Develop multivariate algorithms for high-volume data analysis to find root causes.
• Collaborate with cross-functional teams to debug yield detractors and improve manufacturability.
• Develop tools to transform manufacturing data into actionable yield improvements.
• Execute new product introductions and participate in factory task forces.

Skills

Data analysis

Machine learning

SPC & DOE

Education

PhD in Engineering/Physical Sciences/CS

Master's degree in Engineering/Physical Sciences/CS

Bachelor's degree in Engineering/Physical Sciences/CS

Tools

Semiconductor equipment

Fault isolation tools

Electrical testing

Layout studies

Job description

Intel in Hillsboro, Oregon is seeking an Experienced Hire to join our semiconductor yield analytics team. You will apply statistics, ML, and DOE to drive process innovation, reduce defects, and improve manufacturability across advanced fabrication steps.

You will collaborate with process integration, defect engineering, and design teams to identify root causes, build yield models, and develop tools that convert manufacturing data into actionable improvements for next-generation devices.