Hiring: Transistor Reliability and Quality Engineer Company: Intel Location: Hillsboro, OR Job Posted Time: 2026-09-03 02:23:51 Employment Type: On-site Target Skills & Keywords : Compliance, Machine Learning, Make, Python, R, SQL About the job Required Skills: •Collaborate closely with cross-functional teams including Process Integration, Device Engineering, Yield Engineering, and Product teams to drive quality and reliability excellence from early technology development through technology qualification and high-volume manufacturing readiness. •Drive transistor reliability characterization and certification activities including but not limited to: Hot Carrier Injection (HCI), Bias Temperature Instability (NBTI/PBTI), Time Dependent Dielectric Breakdown (TDDB) •Partner cross-functionally with process integration and device engineering teams to develop a high volume manufacturable technology that meets yield, performance and reliability requirements. •Develop FMEA for novel transistor structures and materials •Define and implement reliability monitors and early warning indicators for technologies •Drive continuous improvement in reliability methodologies, test structures, and characterization techniques •Develop physics-based and empirical reliability models for transistor wear-out and degradation mechanisms including: •Statistical distribution modeling (Weibull, lognormal) Qualifications: •Bachelor's degree in Electrical Engineering, Materials Science, Physics, or a related field with 6+ years of industry experience OR a Master's degree in the above fields with 4+ years of experience OR a Ph.D. with 2+ years of experience. •Applied hands-on capability in semiconductor device fabrication, process characterization, and experimental design. •Proficiency in statistical analysis and data interpretation using tools such as JMP, R, SAS, or Python. •Strong technical background in semiconductor device physics and reliability mechanisms. •Knowledge of process integration and technology development methodologies. •Proven hands-on experience in semiconductor reliability engineering and technology qualification frameworks. •Operational familiarity with advanced CMOS process integration and transistor reliability mechanisms (e.g., HTOL, ELFR, TDDB). •Proficiency in statistical quality systems, process capability analysis, and defect reliability modeling. •Background in data analytics, machine learning, and AI-assisted engineering workflows. •Expertise in semiconductor failure analysis, fabrication, and physical characterization techniques. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!