Define and execute a multi-year strategy for Yield and Defect Engineering, integrating AI/ML, automation, and digital transformation into core workflows.
Lead enterprise-level programs to transition from reactive analysis to predictive and prescriptive yield management systems.
Serve as a thought leader in AI adoption for semiconductor manufacturing, identifying high-value use cases and scaling solutions across sites.
Champion the deployment of AI/Agentic AI solutions to enhance defect detection, classification, excursion prevention, and root cause analysis.
Oversee yield performance across development and high-volume manufacturing, ensuring alignment to aggressive yield, quality, and delivery targets.
Build and lead a high-performing, diverse organization, fostering a culture of innovation, accountability, and continuous learning.

Bachelor's degree in Engineering, Physics, Materials Science, Data Science, or related field (advanced degree preferred).
12+ years of experience in semiconductor manufacturing with deep expertise in yield engineering, defect metrology, or process integration.
Proven track record leading complex, cross-functional programs in high-volume manufacturing environments.
Demonstrated experience driving yield improvement and defect reduction at scale, including ramp and HVM phases.
Strong domain expertise in defect metrology tools, inspection systems, and yield analysis methodologies.
Experience integrating data analytics, machine learning, or AI solutions into engineering workflows.

Yield Development Engineering Manager – Strategic Programs

Key skills