3DIC Yield Analytics & Diagnostics Engineer, Staff

Job Title

3DIC Yield Analytics & Diagnostics Engineer, Staff

Role Summary

Staff-level engineer responsible for yield learning, diagnostics, and data-driven analytics for 2.5D/3DIC, chiplet, and heterogeneous integration products. The role partners with product engineering, design, test, foundry, packaging, assembly, reliability, and OSAT teams to enable root-cause resolution and accelerate yield ramp to high-volume manufacturing.

Experience Level

Senior (Staff). The posting requests multi-year experience in semiconductor yield analytics and diagnostics.

Responsibilities

Drive yield improvement through analytics, diagnostics, and cross-functional problem solving across wafer, package, assembly, and multi-die stack environments.

• Lead yield analytics initiatives for 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 to integrate heterogeneous data sources (wafer sort, final test, package test, reliability, module- and stack-level data).
• Perform advanced diagnostics across chiplets, logic die, stacked DRAM, TSVs, interposers, micro-bumps, hybrid bonding, and package substrates.
• Drive structured root-cause analysis and validate failure mechanisms by correlating electrical, process, design, packaging, and assembly data.
• Analyze memory diagnostics (e.g., SRAM and stacked-DRAM bitmaps) to accelerate failure localization.
• Build analytics frameworks, dashboards, and yield-monitoring methodologies to improve visibility and tracking.
• Apply statistical modeling, machine learning, and AI techniques to accelerate diagnostics and predictive yield learning.
• Collaborate with internal teams and external partners to implement corrective actions and support NPI and HVM.

Requirements

Key technical skills and demonstrated experience required or strongly preferred.

• Must-have: Strong experience in semiconductor yield analytics, diagnostics, and manufacturing data analysis with proven results driving yield improvement in high-volume manufacturing.
• Must-have: Experience analyzing large-scale semiconductor datasets and developing data-driven solutions for complex yield challenges.
• Must-have: Solid understanding of semiconductor test methodologies, failure analysis, and yield learning processes.
• Must-have: Proficiency with analytical tools such as Python, JMP, SQL, Yield Explorer, Power BI, or equivalent platforms.
• Must-have: Strong statistical analysis, problem-solving, and technical leadership skills; effective written and verbal communication for cross-functional collaboration.
• Nice-to-have: Hands-on experience applying AI/ML to yield analytics and diagnostics; experience with DRAM, HBM, stacked-memory diagnostics, and memory bitmap analysis.
• Nice-to-have: Deep understanding of 2.5D/3DIC architectures, chiplet integration, TSV/interposer technologies, hybrid bonding, and advanced packaging flows.
• Nice-to-have: Experience with process correlation, defect characterization, failure-mechanism modeling, and working with OSAT/foundry manufacturing environments.

Education Requirements

The posting specifies degree-plus-experience combinations: a Bachelor's degree in Engineering/Science or related field with 4+ to 6+ years' relevant experience; a Master's degree with approximately 3+ to 5+ years; or a Ph.D. with approximately 2+ to 4+ years, depending on the qualification section.

About the Company

Company: Qualcomm

Headquarters: San Diego, California, United States

Qualcomm is a global leader in semiconductor and telecommunications equipment, specializing in mobile technologies and innovations. Known for its Adreno GPUs, the company provides solutions enabling advancements in mobile gaming, AI, VR/AR, and autonomous driving. Qualcomm's cutting-edge technology and commitment to high-performance, power-efficient designs drive the evolution of mobile graphics and connectivity worldwide.