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Job Summary:
We are seeking a highly motivated and analytical Product Engineering Industrial Engineer (PE IE) to join Micron's Storage Technology and Product Group (STPG) Industrial Engineering team.
This role sits at the intersection of Product Engineering, Manufacturing, Supply Chain, Analytics, Program Management, and Artificial Intelligence. The successful candidate will serve as an end-to-end decision-enablement partner, driving operational excellence across the semiconductor product lifecycle by optimizing product execution, manufacturing readiness, inventory health, cost efficiency, governance, and business performance.
Beyond traditional Industrial Engineering responsibilities, this role will help shape the future operating model of STPG through the application of analytics, automation, AI, and agentic workflows that improve decision quality, execution speed, and organizational productivity. You will partner with cross-functional teams across engineering, manufacturing, planning, supply chain, and business operations to solve complex challenges, influence critical decisions, and enable the successful delivery of next-generation semiconductor technologies.
This is an exceptional opportunity for individuals who enjoy combining engineering, business operations, data analytics, and emerging AI technologies to drive measurable business impact. Successful candidates will gain broad exposure across the product lifecycle while helping scale digital transformation initiatives and operational strategies across a global semiconductor network.
Main Responsibilities
Drive New Product Introduction and Product Lifecycle Execution
- Support products from technology development and engineering builds through qualification, customer sampling, manufacturing ramp, and high-volume production.
- Coordinate execution across Product Engineering, Manufacturing, Planning, Supply Chain, Program Management, and Quality organizations.
- Drive operational readiness, schedule commitments and execution strategies that enable successful product qualification, customer engagement, and manufacturing ramp.
- Identify execution risks early and drive recovery plans to protect key business and customer milestones.
- Enable smooth transitions from development to manufacturing through structured operational readiness planning.
- Influence cross-functional decisions that balance customer commitments, manufacturing constraints, development objectives, and business priorities.
Optimize Inventory and Material Health
- Drive inventory strategy, visibility, and decision-making across engineering and manufacturing networks.
- Identify opportunities to improve inventory utilization, reduce aging inventory, minimize waste, and improve material recoverability.
- Partner with engineering and operations teams to support inventory disposition, reuse, repurpose, consolidation, and recovery activities.
- Develop scalable governance mechanisms that prevent recurring inventory accumulation and improve operational discipline.
Improve Cost and Operational Efficiency
- Lead data-driven initiatives that improve cost competitiveness and operational efficiency by reducing cycle time, inventory exposure, material waste, and overall operating costs.
- Apply structured problem-solving techniques to identify root causes and implement sustainable solutions.
- Drive continuous improvement initiatives that improve productivity, manufacturing efficiency, and business outcomes.
- Quantify business impact and ensure improvements are measurable and sustainable.
Enable Advanced Engineering and Development Programs
- Support complex engineering initiatives, development programs, and advanced technology projects.
- Coordinate operational readiness across engineering, manufacturing, planning, and supply chain organizations.
- Enable operational readiness and scalable execution for next-generation technologies, advanced development programs, and future product platforms.
- Ensure appropriate governance, traceability, and risk management for engineering material and development activities.
Lead Cross-Functional Programs and Change Initiatives
- Lead projects from opportunity identification through implementation and sustainment.
- Align stakeholders across engineering, manufacturing, planning, supply chain, quality, and business teams.
- Facilitate reviews, workshops, issue resolution forums, and executive discussions.
- Drive alignment and influence decision-making across multiple organizations without direct authority.
Drive Operational Excellence and Governance
- Develop scalable processes, operating models, governance frameworks, and business controls.
- Define ownership structures, escalation paths, and accountability mechanisms.
- Establish scalable operating mechanisms, best practices, knowledge systems, and organizational capabilities that improve consistency and execution excellence.
- Promote a culture of continuous improvement, collaboration, and operational excellence.
Deliver Data, Analytics, AI, and Digital Transformation
- Collect, integrate, and analyze data across engineering, manufacturing, planning, and supply chain ecosystems.
- Develop dashboards, KPIs, predictive analytics, business intelligence solutions, and decision-support capabilities.
- Translate complex data into actionable insights, risk signals, recommendations, and executive-level decision support.
- Identify and implement opportunities to improve business outcomes through analytics, AI, automation, and digital technologies.
- Design and deploy scalable AI-enabled applications, workflow automations, and agentic solutions supporting operational planning, inventory management, risk detection, reporting, and execution.
- Establish governance and change-management practices that enable responsible, sustainable, and measurable adoption of digital and AI-enabled capabilities.
AI 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.
Other Responsibilities:
- Faster and more predictable new product introductions.
- Improved operational readiness and execution performance.
- Lower inventory exposure and improved inventory health.
- Reduced cost, cycle time, and process waste.
- Earlier identification and mitigation of business risks.
- Improved decision quality through analytics and AI-enabled insights.
- Successful deployment of digital, automated, and agentic workflows.
- Stronger cross-functional collaboration and ownership alignment.
- Sustainable processes supported by governance, documentation, and accountability.
Minimum Required Qualifications/Experience
- Bachelor's degree in Electronics & Electrical Engineering, Mechanical Engineering, Industrial Engineering, Manufacturing Engineering or a related technical discipline.
- Experience in semiconductor manufacturing, product engineering, industrial engineering, supply chain, planning, operations, analytics, or related technical functions.
- Experience supporting New Product Introduction (NPI), product lifecycle management, manufacturing operations, inventory management, or operational excellence initiatives.
- Demonstrated experience leading or supporting cross-functional projects, process improvements, or business transformation initiatives.
- Experience developing analytics solutions, dashboards, reporting platforms, workflow automations, or decision-support systems.
Highly Desirable/Preferred skills or experience
- Strong analytical, data interpretation, and structured problem-solving capabilities.
- Excellent communication, stakeholder management, influencing, and cross-functional collaboration skills.
- Ability to translate complex data into actionable insights, business recommendations, and executive-level communications.
- Ability to think systematically across engineering, manufacturing, supply chain, and business processes while balancing competing objectives and constraints.
- Experience applying AI, analytics, automation, or digital solutions to improve business processes, decision-making, operational efficiency, or organizational productivity. Familiarity with Microsoft Copilot, Claude Code, or similar AI-enabled technologies is advantageous.
- Familiarity with SAP, MES, planning, manufacturing execution, or operational data platforms.
- Strong project management, prioritization, and change-management