Staff Yield Engineer
NOKIA | |
United States, California, San Jose | |
6373 San Ignacio Avenue (Show on map) | |
Jul 13, 2026 | |
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Role Summary We are seeking a Staff Yield Engineer to lead yield improvement initiatives and develop scalable process control methodologies for a rapidly growing InP photonic integrated circuit (PIC) wafer fab. This role operates with a high degree of independence in a fast-paced manufacturing environment, driving complex technical issues from problem identification through sustainable corrective actions. Working closely with Integration, Process, Equipment, and Manufacturing Operations, the engineer will play a key role in improving fab yield performance, enabling Fab2 ramp readiness, and strengthening manufacturing quality systems. Key Responsibilities Lead Yield Improvement Lead yield improvement initiatives by identifying key yield detractors, prioritizing improvement opportunities, and driving structured problem-solving to improve fab performance and manufacturing robustness. Process Control Develop and deploy practical process control methodologies and control plans to reduce process variation and support stable high-volume manufacturing. Support new product ramp readiness by translating proven process control methodologies and manufacturing best practices from Fab to Fab into scalable monitoring and control frameworks. Root Cause Investigation Support root cause investigations for critical yield excursions and complex manufacturing issues by applying structured engineering analysis, manufacturing data, and appropriate analytical techniques to identify effective corrective and preventive actions. Cross-functional Execution Drive cross-functional resolution of critical yield excursions, wafer scrap, and quality incidents by coordinating Integration, Process, Equipment, Facilities, and Manufacturing teams using structured 8D methodology. Demonstrate strong ownership, urgency, and execution discipline to ensure timely and sustainable closure. Quality Governance Contribute to continuous improvement of manufacturing quality systems by strengthening SPC methodology, excursion management, control plan execution, data visibility, and quality governance practices. Qualifications
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Jul 13, 2026