Spec Gas/ Specs Chem Global Supplier Quality Engineering (SQE) Engineer

Micron Technology • Boise, ID

17d • Onsite

About The Position

Micron Technology is a world leader in memory and storage solutions. This role focuses on ensuring the quality of specialized gases and chemicals used in semiconductor manufacturing. The engineer will collaborate with development teams, suppliers, and cross-functional groups to define specifications, assess risks, and implement quality programs. A key aspect of this role involves leveraging AI/ML-driven analytics and digital tools to enhance supplier capabilities, predict failures, and accelerate qualification processes. The position requires strong communication, problem-solving, and a commitment to continuous improvement, with opportunities to contribute to supplier digitalization and AI use case development.

Requirements

• Experience in Supplier Quality Engineering (SQE) or related field.
• Familiarity with semiconductor manufacturing processes and materials.
• Understanding of quality risk assessments and mitigation strategies.
• Experience with data analytics, predictive modeling, and AI/ML concepts.
• Proficiency in utilizing digital tools and platforms for data analysis and reporting.
• Strong communication and presentation skills.
• Ability to lead cross-functional teams and facilitate meetings.
• Experience in managing supplier relationships and performance.
• Knowledge of quality management systems and standards.
• Ability to work independently and take ownership of tasks.
• Strong commitment to quality, accuracy, and timeliness.
• Initiative and self-motivation.
• AI/data literacy, including understanding of ML models, data pipelines, and digital tools.

Nice To Haves

• Experience with specialized gases and chemicals in semiconductor manufacturing.
• Experience with First of a Kind (FOAK) materials and new technode development.
• Experience with AI-driven analytics, AI-based risk scoring models, and digital dashboards.
• Experience with AI-assisted scenario modeling and AI-assisted pattern recognition.
• Experience with AI-driven root cause analysis tools.
• Experience with AI-assisted reporting tools and visualization platforms.
• Experience in supplier digitalization programs and AI/ML adoption in supplier quality.
• Experience in developing AI use cases (predictive quality, smart SPC, automated audits, supplier risk intelligence).
• Experience in driving innovation in digital quality ecosystems.

Responsibilities

• Collaborate with the TD team on First of a Kind (FOAK) Materials Quality Readiness, Supplier Quality Programs, and Specification definition.
• Leverage AI/ML-driven analytics to assess FOAK material risks, predict failure modes, and accelerate qualification readiness.
• Participate, support, and recommend from a Quality perspective on FOAK materials sourcing strategies.
• Utilize data-driven insights and predictive modeling to enhance supplier capability assessments and sourcing decisions.
• Support cross-fab technology transfer activities regarding New Technology BOM and drive supplier Quality programs.
• Lead cross-functional Category Strategy Team meetings to fan out lessons learned from HVM issues to R&D, align on FOAK materials strategy, and ensure closed-loop communication.
• Apply AI-enabled knowledge management systems to systematically capture, classify, and disseminate lessons learned across global sites.
• 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.
• 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).
• Lead the definition and alignment of global material specifications for Specs Gas & Specs Chem.
• 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 the Quality Roadmap (e.g., predictive excursion detection, automated SPC monitoring, anomaly detection).
• Implement quality programs, benchmarking, and preventive controls aligned with 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 through SCM process.
• Oversee resolution of globally impacting photochemical 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.
• Provide weekly updates on 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.
• Take ownership and accountability for achieving goals and completing actions.
• Establish measurable development objectives aligned with corporate priorities.
• Leverage coaching and mentorship for growth.
• Manage time and resources effectively.
• Reflect and continuously improve performance.
• Demonstrate strong commitment to quality and deliver with accuracy and timeliness.
• Show initiative and self-motivation.
• 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.
• Collaborate with global SQEs and cross-regional teams on category initiatives.
• Serve as a key SME 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.

Benefits

• Choice of medical, dental and vision plans
• Benefit programs that help protect your income if you are unable to work due to illness or injury
• Paid family leave
• Robust paid time-off program
• Paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed