Yield & Process Optimization Engineer

Samsung Electronics Perú; Austin (TX); On-site; USD 95,000 - 120,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) matching

Onsite cafe and wellness facilities

Job summary

Samsung Austin Semiconductor is seeking a highly analytical Yield and PCI Engineer to monitor wafer manufacturing processes, drive yield improvements, and investigate excursions. You will use SPC, defect data, and parametric results to identify root causes and implement robust solutions with Process, Equipment, and Integration teams.

The role emphasizes predictive modeling, baseline forecasting, and advanced data analytics using Python, JMP, and SQL to enhance yield and stability across advanced

Qualifications

• BS or MS in electrical engineering or related field required.
• Strong understanding of semiconductor device physics and CMOS processes.
• Experience with data mining and advanced analytics in manufacturing.

Responsibilities

• Predictive yield modeling using inline metrology, defect data, and FDC metrics.
• Baseline forecasting of yield trajectories for ramping and mature nodes.
• Drive end-to-end yield improvement across tests and data sources.
• Lead root cause analysis linking electrical signatures to defects.
• Apply data science and ML to build yield models and analytics pipelines.
• Lead yield management, KPIs, and communicate risks to leadership.

Skills

SPC

Statistical data analysis

Root cause analysis

Python

SQL

JMP

Machine learning

Data mining

Cross-functional leadership

Communication

Education

B.E./M.Sc. in Electrical Engineering or related field

Tools

Python

JMP

SQL

Job description

Samsung Austin Semiconductor is seeking a highly analytical Yield and PCI Engineer to monitor wafer manufacturing processes, drive yield improvements, and investigate excursions. You will use SPC, defect data, and parametric results to identify root causes and implement robust solutions with Process, Equipment, and Integration teams.

The role emphasizes predictive modeling, baseline forecasting, and advanced data analytics using Python, JMP, and SQL to enhance yield and stability across advanced