3DIC Yield Analytics & Diagnostics Engineer, Staff

## Company: Qualcomm Semiconductor Limited ## Job Area: Engineering Group, Engineering Group > ASICS Engineering General Summary: We are seeking a highly motivated and experienced 3DIC Yield Analytics & Diagnostics Engineer, Staff to drive yield learning and diagnostics for next-generation 2.5D, 3DIC, chiplet, and heterogeneous integration technologies. This role focuses on leveraging advanced analytics, diagnostics methodologies, and large-scale semiconductor datasets to accelerate yield ramp, identify systematic yield limiters, and enable rapid root-cause resolution across wafer, package, assembly, and multi-die stack environments. The successful candidate will work closely with Product Engineering, Design, Test, Foundry, Packaging, Assembly, Reliability, and OSAT partners to develop scalable yield analytics frameworks and diagnostic methodologies that improve product quality, manufacturing efficiency, and time-to-volume. Key Responsibilities * Lead 3DIC yield analytics initiatives to drive systematic yield improvement across wafer fabrication, advanced packaging, assembly, and test operations. * Analyze large-scale yield and diagnostics datasets to identify systematic, random, and parametric failure mechanisms. * Develop and scale methodologies for analyzing heterogeneous data sources, including wafer sort, final test, package test, reliability, module-level, and stack-level data. * Perform advanced diagnostics to isolate failure mechanisms across chiplets, logic die, stacked DRAM, TSVs, interposers, micro-bumps, hybrid bonding interfaces, and package substrates. * Drive structured root-cause analysis (RCA) and validate failure mechanisms through correlation of electrical, process, design, packaging, and assembly data. * Analyze memory diagnostics data, including SRAM and stacked-DRAM bitmap analysis, to accelerate yield learning and failure localization. * Develop analytics frameworks, dashboards, and yield-monitoring methodologies to improve product and manufacturing visibility. * Apply statistical modeling, machine learning, and AI techniques to accelerate diagnostics, identify yield risks, and improve predictive yield learning. * Collaborate with cross-functional teams and external partners to implement corrective actions and drive continuous yield improvement. * Support New Product Introduction (NPI) and high-volume manufacturing (HVM) by identifying yield risks and establishing robust monitoring strategies. Qualifications * Bachelor's degree in Engineering or related field with 6+ years of relevant experience, OR Master's degree with 5+ years, OR Ph.D. with 4+ years. * Strong experience in semiconductor yield analytics, diagnostics, and manufacturing data analysis. * Proven track record of driving yield improvement in high-volume manufacturing environments. * Experience analyzing large-scale semiconductor datasets and developing data-driven solutions for complex yield challenges. * Strong understanding of semiconductor test methodologies, failure analysis, and yield learning processes. * Proficiency with analytical tools such as Python, JMP, SQL, Yield Explorer, Power BI, or equivalent platforms. * Strong statistical analysis, problem-solving, and technical leadership skills. * Excellent communication and cross-functional collaboration abilities. 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...