Senior/Staff Engineer, FE Labor Prod, Data Engineering

Eightfold

Senior/Staff Engineer driving FE labor productivity and implementing AI strategies at Micron Technology. Leading productivity improvements and operational efficiency in semiconductor operations.

Posted 4/25/2026full-timeTaoyuan • 🇹🇼 TaiwanSeniorWebsite

Tech Stack

Tools & technologies

SQL

About the role

Key responsibilities & impact

Drive year over year improvement in FE labor productivity VAM/HC in support of the 5MORE productivity roadmap.
Lead E2E execution and governance of FE labor productivity programs to ensure on time delivery and measurable outcomes.
Standardize tools, methods, and processes across sites to enable scalable and repeatable execution aligned with enterprise goals.
Integrate labor initiatives across AI, automation, robotics, DREAM team, and innovation programs into a cohesive execution plan.
Track, validate, and report productivity benefits including labor hour reduction, VAM/HC, and annualized savings in partnership with Site’s Labor Champions & Finance team.
Maintain and optimize the loading-based staffing (LBS) model to align staffing levels with actual workload demand.
Provide governance support for SEAL and SWAT initiatives.
Lead Labor SWAT initiatives to improve FE labor productivity and functional AI roadmap.
Monitor labor performance metrics, identify gaps, benchmark best practices, and support performance recovery actions when needed.
Enable cross site knowledge sharing to scale successful solutions and maximize network impact.
Guide site and central teams to identify and prioritize productivity opportunities using AWMS workload data to convert effort into measurable time savings.
Managing programs involving pipelines of AI, GenAI, automation, and low code solutions, including copilots, digital footprint, and workflow automation.
Support development and execution of functional AI roadmaps across FE organizations with focus on reuse and scalability.
Drive structured use case intake, value assessment, feasibility review, and deployment planning to ensure sustainable adoption.
Develop KPI dashboards and management reporting to provide visibility into progress, adoption, and realized benefits.
Translate data into actionable insights to support fact-based prioritization and decision making.
Support workload forecasting, productivity baselining, and scenario modeling by coordinating requirements and validating outputs with stakeholders.

Requirements

What you’ll need

Degree in Engineering, Industrial Engineering, Statistics, or a related field
At least 3+ years of experience in semiconductor operations.
Strong program management skills (portfolio planning, governance, benefits realization, dependency management, change management).
Preferred experience leading programs/projects with demonstrated outcomes in productivity, operational efficiency, or workforce/labor optimization.
Working knowledge of GenAI concepts and delivery (use-case framing, prompt/workflow design basics, evaluation of value and risk, adoption metrics).
Experience delivering automation and low-code solutions (e.g., Power Automate, Copilot Studio, UiPath, SQL or similar), including requirements-to-deployment lifecycle.
Strong analytical capability (KPIs, dashboards, baseline/benefits tracking); able to translate data into decisions and execution plans.
Excellent communication and stakeholder management skills across site, central, and executive audiences.
Proficiency with Microsoft 365 (Excel/PowerPoint/Teams) and data visualization tools (e.g., Power BI).

Benefits

Comp & perks

Health insurance
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

program managementproductivity optimizationoperational efficiencydata analysisautomation solutionslow-code solutionsKPI developmentworkload forecastingscenario modelinglabor productivity metrics

Soft Skills

communicationstakeholder managementanalytical capabilitygovernance supportcross-site collaborationdecision makingchange managementleadershipprioritizationknowledge sharing