Principal Reliability Engineer
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Before you apply
LocationJhubei City, Taiwan
Work modeon-site
SeniorityLead
Experience5+ yrs
Company size1,001–5,000 people
PostedSep 2, 2026 · 2mo ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, Systems Engineering, Manufacturing Engineering, Physics, or a related technical discipline
5+ years of experience in semiconductor equipment, semiconductor manufacturing, equipment reliability, systems engineering, or a related field
Direct experience working in a semiconductor fab environment
Strong understanding of semiconductor manufacturing equipment and production processes
Demonstrated experience with data analysis, statistical methods, and structured problem-solving
Experience analyzing equipment performance, reliability, or manufacturing yield data
Minimum of 5 years of related experience with a Bachelor's degree; or 3 years and a Master's degree; or a PhD without experience; or equivalent work
Experience with equipment reliability engineering and field performance monitoring
Knowledge of SPC, GR&R, DOE, FMEA, Weibull analysis, and statistical process control
Experience developing automated dashboards or analytical tools using Python, MATLAB, SQL, Power BI, or similar tools
Experience with semiconductor equipment interfaces, equipment logs, alarms, sensors, and trace data
Experience with yield management and correlation of equipment parameters to wafer-level performance
Experience supporting new tool introduction, installation, qualification, and production ramp
Skills
Python
MATLAB
SQL
Power BI
Forming Our Future together
FormFactor, Inc. (NASDAQ: FORM), is a leading provider of essential test and measurement technologies along the full semiconductor product life cycle — from characterization, modeling, reliability, and design de-bug, to qualification and production test. Semiconductor companies rely upon FormFactor’s products and services to accelerate profitability by optimizing device performance and advancing yield knowledge. The company serves customers through its network of facilities in Asia, Europe, and North America.
Rooted in our core values — Focus on the Customer, Ownership & Accountability, Respectfully & Effectively Communicate, and Motivate & Develop People — we foster an environment where diverse perspectives are not only welcomed but celebrated. Everyone can make an impact here. Whether it’s improving products, supporting customers, or positively influencing peers and the community, the contributions of our people matter.
Job Description:
Requirements
Bachelor’s or Master’s degree in Mechanical Engineering, Electrical Engineering, Systems Engineering, Manufacturing Engineering, Physics, or a related technical discipline.
5+ years of experience in semiconductor equipment, semiconductor manufacturing, equipment reliability, systems engineering, or a related field.
Direct experience working in a semiconductor fab environment.
Strong understanding of semiconductor manufacturing equipment and production processes.
Demonstrated experience with data analysis, statistical methods, and structured problem-solving.
Experience analyzing equipment performance, reliability, or manufacturing yield data.
Experience with equipment reliability engineering and field performance monitoring.
Knowledge of SPC, GR&R, DOE, FMEA, Weibull analysis, and statistical process control.
Experience developing automated dashboards or analytical tools using Python, MATLAB, SQL, Power BI, or similar tools.
Experience with semiconductor equipment interfaces, equipment logs, alarms, sensors, and trace data.
Experience with yield management and correlation of equipment parameters to wafer-level performance.
Experience supporting new tool introduction, installation, qualification, and production ramp.
Contribute to continuous improvement of test methods, customer experience, and integration processes.
Provide data-driven recommendations for product improvements and next-generation tool designs.
Identify sources of tool-to-tool variations & correlate tool parameters, environmental conditions, maintenance events, alarms, and equipment states with wafer performance.
Root-cause investigations using structured methodologies such as 8D, Fault-tree analysis, Fishbone analysis, Pareto analysis, DOE
SPC
FMEA
Skills:
Education & Experience:
Minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD without experience; or equivalent work | Required