FE Supplier Quality Manager (Gas/Target)

Overview

• Our vision is to transform how the world uses information to enrich life for all .
• Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.
• HVM Phase Sourcing, Selection, and Qualification Lead quality risk assessments and implement mitigation strategies to support qualification activities.
• Deploy AI-based risk scoring models and digital dashboards to prioritize qualification risks and drive faster decision-making.
• Provide quality-focused input on sourcing and segmentation strategies, including business continuity planning, benchmarking, and supplier selection.
• Incorporate advanced analytics and AI-assisted scenario modeling into RFQ/RFI and supplier selection processes.
• Conduct technical risk assessment audits for new suppliers and materials to evaluate capability and readiness for HVM.
• Leverage digital audit tools and AI-assisted pattern recognition to identify systemic risks and hidden gaps.
• Establish, communicate, and ensure compliance with Supplier Requirements Standards (SRS).
• Support cross fab technology transfer activities in terms of new technology Bill of Materials (BOM) and driving global specifications alignment.
• Supplier Development and Excursion Management Lead the definition and alignment of global material specifications for Target and Specs Gas categories Support development of smart specifications by integrating AI-driven process capability insights and predictive limits.
• Support Material Category Leads in shaping Category Quality Strategy, including Quality Roadmap and Defense Line Program.
• Embed AI/ML use cases into Quality Roadmap (e.g., predictive excursion detection, automated SPC monitoring, anomaly detection).
• Deploy Quality programs, lessons learnt and benchmark to/ with suppliers to ensure controls and preventive measures are in place to support Shift-Left-Strategy.
• Facilitate regular Quality and Technical Review (QTR) meetings with suppliers.
• Introduce data visualization and AI-assisted insights into QTRs to drive fact-based discussions and proactive actions.
• Manage supplier and sub-supplier changes in Supplier Change Management (SCM).
• Oversee resolution of globally impacting Target and Spec Gas quality issues.
• Utilize AI-driven root cause analysis tools (e.g., pattern mining, correlation analytics) to accelerate issue resolution.
• Collaborate with OCT MTE, Operations, and Facility teams for deep-dive investigations and implement corrective/preventive actions.
• Cascade lessons learned globally to ensure closed-loop prevention.
• Define, track, and monitor monthly supplier quality performance metrics and SRS compliance.
• Develop automated dashboards and AI-enabled performance monitoring systems for real-time supplier scorecards and predictive alerts.
• Continuously improve supplier quality processes to enhance productivity and efficiency.
• Partner with Procurement on supplier evaluations using quality metrics.
• Enable data integration across systems and apply AI analytics to drive objective, data-driven supplier decisions.
• Communication & Presentation Provide weekly updates on the status and progress of all supplier-related activities.
• Maintain strong communication with Global Quality, Procurement, OCT, and cross-functional teams.
• Respond to issues promptly with appropriate escalation.
• Keep stakeholders informed of progress, risks, and opportunities.
• Leverage AI-assisted reporting tools to generate concise, data-driven insights and executive-ready summaries.
• Utilize visualization platforms and automated storytelling tools to enhance clarity and decision-making.
• Training and Development Take ownership and accountability for achieving goals and completing actions.
• Establish clear, measurable personal development and performance objectives aligned with departmental and corporate priorities.
• Leverage guidance from coaches and mentors to build the skills necessary for your next career steps.
• Manage time and resources efficiently to maximize productivity.
• Continuously reflect on your performance, approach, and goals to drive improvement.
• Demonstrate a strong commitment to quality in all aspects of your work.
• Deliver assignments with accuracy, thoroughness, and timeliness.
• Show initiative and self-motivation in completing tasks, training, and projects.
• Continuously build AI/data literacy (e.g., understanding ML models, data pipelines, and digital tools) to enhance quality engineering effectiveness.
• Adopt and champion AI-enabled tools and digital workflows within SQE processes.
• Growth Opportunity Collaborate with global SQEs and cross-regional teams on category initiatives.
• Serve as a key subject matter expert in supplier digitalization programs, contributing insights and guidance on AI/ML adoption in supplier quality.
• Lead or participate in development of AI use cases (predictive quality, smart SPC, automated audits, supplier risk intelligence).
• Build deep expertise in material criticality by acting as a primary liaison with suppliers.
• Drive innovation in digital quality ecosystems, including data integration, automation, and AI-enabled supplier collaboration platforms.
• Education: Master’s degree or bachelor’s Degree in Chemical/ Chemistry/ Material Engineering or Related Field.
• Experiences: Minimum 5 years of experience in the semiconductor industry or a high-volume manufacturing environment is highly advantageous.
• Proven experience in supplier quality management, with the ability to effectively manage and drive performance improvement across global suppliers and international supply chains.
• Demonstrated ability to collaborate effectively with cross-functional and global teams, including Manufacturing, Procurement, Engineering, Quality, and Supply Chain organizations.
• Strong problem-solving, stakeholder management, and communication skills with the capability to influence and drive quality improvements across a global supplier network.
• Exposure to incoming material control (IQC), or manufacturing quality processes is an added advantage.
• Experience in semiconductor manufacturing processes, wafer fabrication, or related process engineering disciplines is preferred.
• Basic familiarity with ISO 9001 and IATF 16949 quality management system standards and their application in manufacturing environments.
• Ability to utilize data analytics and AI insights to assess material risks, performance trends, and variability.
• Experience leveraging digital/AI-driven tools to improve quality performance, yield, or supplier management is a plus.