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Micron Technology

Makes memory and storage chips for AI and PCs

FE Supplier Quality Manager - Gas, Target

Quality EngineeringConfirmed live in the last 24 hours
Full-timeBoise, ID, USANo salary listedIn-person

About the Job

Requirements

  • A master's or bachelor's degree in Chemical Engineering, Chemistry, Material Engineering, or a related field.
  • At least 5 years of experience in the semiconductor industry or a high-volume manufacturing environment is highly advantageous.
  • Proven experience in supplier quality management and the ability to manage and improve performance across global suppliers and international supply chains.
  • Ability to collaborate with cross-functional and global Manufacturing, Procurement, Engineering, Quality, and Supply Chain teams.
  • Problem-solving, stakeholder management, and communication skills, with the ability to influence and drive quality improvements across a global supplier network.
  • Basic familiarity with ISO 9001 and IATF 16949 quality management system standards and their application in manufacturing environments.
  • Ability to use data analytics and AI insights to assess material risks, performance trends, and variability.
  • Proficiency in Microsoft Office Suite, including PowerPoint, Word, Excel, and OneNote.
  • Experience with data visualization tools such as Power BI and AI-assisted productivity tools to generate insights, dashboards, and executive summaries.
  • Ability to work independently in a dynamic, fast-paced environment and apply data-driven and AI-assisted decision-making with minimal supervision.
  • Ability to engage stakeholders at all levels and translate AI/data insights into clear, actionable recommendations for technical and non-technical audiences.
  • Hands-on experience with Measurement System Analysis (MSA) and calibration; Statistical Process Control (SPC) and FMEA; problem-solving methodologies; quality management systems; and advanced analytics or AI/ML techniques such as anomaly detection, predictive modeling, and trend analysis for root cause analysis and process control.

Responsibilities

  • 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 support 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 high-volume manufacturing.
  • Use 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 involving new-technology Bills of Materials (BOM) and global specification alignment.
  • 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 the Quality Roadmap and Defense Line Program.
  • Embed AI/ML use cases into the Quality Roadmap, including predictive excursion detection, automated SPC monitoring, and anomaly detection.
  • Deploy quality programs, lessons learned, and benchmarks with suppliers to ensure controls and preventive measures support the Shift-Left Strategy.
  • Facilitate regular Quality and Technical Review (QTR) meetings with suppliers.
  • Introduce data visualization and AI-assisted insights into QTRs to support fact-based discussion and proactive action.
  • Manage supplier and sub-supplier changes through Supplier Change Management (SCM).
  • Oversee resolution of globally impacting Target and Spec Gas quality issues.
  • Use AI-driven root-cause analysis tools, including pattern mining and correlation analytics, to accelerate issue resolution.
  • Collaborate with OCT MTE, Operations, and Facility teams on in-depth investigations and implement corrective and 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 support objective, data-driven supplier decisions.
  • Provide weekly updates on the status and progress of supplier-related activities.
  • Maintain communication with Global Quality, Procurement, OCT, and cross-functional teams; respond promptly to issues with appropriate escalation and keep stakeholders informed of progress, risks, and opportunities.
  • Use AI-assisted reporting tools to generate concise, data-driven insights and executive-ready summaries.
  • Use visualization platforms and automated storytelling tools to improve clarity and decision-making.
  • Take ownership and accountability for achieving goals and completing actions; establish measurable personal development and performance objectives aligned with departmental and corporate priorities.
  • Use guidance from coaches and mentors to build skills for future career steps; manage time and resources efficiently; reflect on performance, approach, and goals to drive improvement.
  • Demonstrate commitment to quality and deliver assignments accurately, thoroughly, and on time; show initiative and self-motivation in completing tasks, training, and projects.
  • Build AI/data literacy, including understanding ML models, data pipelines, and digital tools, to improve quality-engineering effectiveness.
  • Adopt and champion AI-enabled tools and digital workflows within Supplier Quality Engineering (SQE) processes.
  • Collaborate with global SQEs and cross-regional teams on category initiatives.
  • Serve as a subject matter expert in supplier digitalization programs and contribute insights and guidance on AI/ML adoption in supplier quality.
  • Lead or participate in development of AI use cases, including predictive quality, smart SPC, automated audits, and supplier risk intelligence.
  • Build 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.

Desired Qualifications

  • Exposure to incoming material control (IQC) or manufacturing quality processes.
  • Experience in semiconductor manufacturing processes, wafer fabrication, or related process engineering disciplines.
  • Experience leveraging digital/AI-driven tools to improve quality performance, yield, or supplier management.
  • Experience applying AI/ML models or advanced analytics to quality analytics, supplier performance monitoring, or excursion management.
  • Familiarity with data pipelines, automation, and digital dashboards for real-time monitoring and decision-making.
  • Ability to integrate multiple data sources, including supplier, fab, and metrology data, to drive insights and continuous improvement.

About the Company

Micron Technology

Makes memory and storage chips for AI and PCs

Micron Technology designs and manufactures memory and storage chips, mainly DRAM and NAND flash, used in data centers, PCs, phones, cars and industrial equipment. It is one of only three companies that make HBM, the stacked high-bandwidth memory placed beside processors in AI servers, and it is the largest memory chipmaker based in the United States. Unlike chip designers that outsource production, Micron runs its own fabs and assembly sites in the United States and across Asia. It earns money by selling chips, memory modules and solid-state drives to cloud providers, device makers and distributors. Micron was founded in 1978 and is headquartered in Boise, Idaho.

Company size
10,001+
Company stage
IPO
Headquarters
Boise, ID
Founded
1978

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