Our vision is to transform how the world uses information to enrich life for all.
Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
As a Quality Metro Real-time Defect Analysis (RDA) Engineer, you will be responsible for enabling robust quality monitoring, early detection, and rapid containment of quality risks across advanced packaging and NPI manufacturing environments.
You will focus on leveraging RDA platforms, Statistical Process Control/ Fault Detection & Classification (SPC)/ (FDC) systems, automation, and data analytics to prevent escapes, accelerate learning, and improve product and process robustness, particularly during N ew Product Introduction(NPI) , pilot, and early ramp phases. This role acts as a critical bridge between Quality, RDA, Process, Equipment, and NPI teams, ensuring quality requirements are embedded into monitoring strategies and operational execution.
You will work closely with Site and Global Quality, Process Integration, Equipment Engineering, and Automation teams to drive quality-focused diagnostics, excursion management, and continuous improvement in a high-change, high-learning environment.
Identify, Select, and Deliver Quality-Centric RDA Processes, Monitoring, and Technology
- Define and sustain quality-focused monitoring strategies using RDA, SPC, FDC, and advanced analytics for advanced packaging processes
- Identify critical quality signals, failure modes, and process sensitivities, particularly for NPI and new package introductions
- Translate quality risks and requirements into actionable RDA rules, alarms, dashboards, and control strategies
- Support early detection and prevention of quality excursions, yield detractors, and systemic risks
- Partner with Quality and Process teams to continuously refine monitoring thresholds and response strategies as NPI matures
- Ensure quality considerations are embedded in new RDA capability deployments and automation enhancements
Support Quality Readiness for NPI, Pilot, and Ramp-to- High Volume Manufacturing (HVM) Transitions
- Support quality readiness assessments for new tools, processes, and package types through RDA and data visibility
- Collaborate with NPI, Process, and Equipment teams to ensure monitoring coverage for critical-to-quality (CTQ) parameters
- Provide data-driven insights to support NPI reviews, risk assessments, and ramp decisions
- Validate monitoring effectiveness during pilot and early ramp phases and drive improvements as needed
- Support containment, disposition, and recovery activities during NPI-related quality events
Drive, Improve and Maintain Quality Metrics and Excursion Management Effectiveness
- Monitor and analyze quality-related metrics such as excursion rate, detection effectiveness, response time, and escape prevention
- Support root cause investigations by providing high-quality data, trends, and diagnostic insights from RDA systems
- Ensure accurate logging, documentation, and traceability of quality events and corrective actions
- Identify recurring quality issues and systemic gaps in monitoring or response mechanisms
- Proactively escalate high-risk trends and quality concerns with clear data and impact assessment
Collaborating on Continuous Improvement and Quality System Integration
- Partner with Site and Global Quality teams to align RDA monitoring strategies with quality systems and standards
- Support continuous improvement initiatives focused on yield improvement, defect reduction, and robustness enhancement
- Provide operational and technical feedback on RDA solutions from a quality effectiveness perspective
- Participate in lessons learned, best practice sharing, and standardization efforts across sites and programs
- Support audits, reviews, and assessments by providing objective monitoring data and quality insights
Job Responsibilities:
- Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
- Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one's scope of work.
Job Requirements / Qualifications
- Bachelor's degree in engineering (Chemical, Materials, Electrical, Mechanical, Industrial, Computer Engineering, or related discipline)
- 0-2 years of experience in semiconductor manufacturing, advanced packaging, quality engineering, process engineering, or RDA/automation roles
- Strong experience supporting NPI, pilot lines, or early production ramps
- Solid understanding of semiconductor quality c