Bachelor's degree in Science, Engineering, or a related field with 4+ years of relevant experience; alternatively, a Master's degree with 3+ years or a PhD with 2+ years of relevant experience.
Required Previous Experiences
Experience in semiconductor yield analytics, diagnostics, and manufacturing data analysis
Experience driving yield improvement in high-volume manufacturing environments
Experience analyzing large-scale semiconductor datasets and developing data-driven solutions for complex yield challenges
Experience with semiconductor test methodologies, failure analysis, and yield learning processes
4+ years of ASIC design, verification, validation, integration, or related work experience
Preferred Qualifications
Deep understanding of 2.5D/3DIC architectures, chiplet integration, TSV/interposer technologies, hybrid bonding, and advanced packaging flows
Experience building and scaling yield analytics frameworks, diagnostics methodologies, and data infrastructure
Familiarity with process correlation, defect characterization, and failure-mechanism modeling
Experience working with advanced packaging, assembly, OSAT, and foundry manufacturing environments
Hands-on experience applying AI/ML techniques to semiconductor yield analytics and diagnostics
Experience with DRAM, HBM, and stacked-memory diagnostics
Knowledge of package reliability, failure analysis, and heterogeneous integration challenges
Demonstrated technical leadership and ability to drive cross-functional yield improvement initiatives
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