Monitor yield performance and develop dashboards, KPIs, and automated reporting solutions for manufacturing health assessment.
Support New Product Introduction (NPI) activities through yield risk assessments, characterization, and early-stage silicon learning.
Utilize statistical analysis and data mining techniques to identify process-related yield limiters and drive corrective actions.
Develop predictive yield models to support capacity planning, business forecasting, and supply chain decision-making.
Work cross-functionally with Design, DFT, Test, Product Engineering, and Quality teams to improve product robustness and manufacturability.
Drive continuous improvement through advanced analytics, automation, and AI/ML-based yield solutions.
Qualifications
M.S. or Ph.D. in Electrical Engineering, Semiconductor Physics, Materials Science, or a related field.
5+ years of semiconductor industry experience in Process Integration, Yield Engineering, Product Engineering, Technology Development, or Yield Diagnostics.
Hands-on experience with advanced technology nodes (3nm, 2nm, or equivalent) and yield improvement activities.
Strong understanding of semiconductor fabrication processes, including lithography, etch, deposition, CMP, device integration, and interconnect technologies.
Experience in process-yield correlation, yield analysis, failure diagnostics, and manufacturing data analytics.
Familiarity with digital product architecture, DFT methodologies, and semiconductor test flows.
Proficiency in JMP, Yield Explorer, Python, SQL, Excel, Power BI, or similar data analysis tools.
Strong analytical and problem-solving skills with the ability to drive complex root-cause investigations.
Excellent communication skills and ability to work effectively across global and cross-functional teams.
Preferred Qualifications
Experience with advanced-node process development and yield ramp activities.
Strong knowledge of PCM structures, inline defect monitoring, process control methodologies, and metrology systems.
Experience working directly with foundry partners on process optimization and yield improvement.
Familiarity with scan diagnosis tools and digital failure analysis techniques.
Experience applying machine learning and AI techniques to semiconductor yield analytics.
Proven track record of driving yield improvement in high-volume manufacturing environments.
Why Join Us
This position offers a unique opportunity to work at the forefront of semiconductor technology, driving process learning and yield optimization for industry-leading advanced-node products. You will play a critical role in enabling successful technology ramps, improving manufacturing efficiency, and delivering world-class product quality.
Minimum Qualifications
- Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
- OR
- Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
- OR
- PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
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