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Micron Technology

Makes memory and storage chips for AI and PCs

GQ Ops IE Modeling and Automation Engineer

Manufacturing EngineeringConfirmed live in the last 24 hours
Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or higher in Industrial Engineering, Automation, Mechatronics, Electrical and Electronics, Mechanical Engineering, Computer Science, Data Science, or a related technical field.
  • Experience in automation, industrial engineering, manufacturing systems, planning, capacity modeling, data analytics, process improvement, or system deployment.
  • Strong understanding of AMHS, equipment automation, capacity planning, throughput, cycle time, bottleneck analysis, and productivity improvement.
  • Experience with data analysis or reporting tools such as Excel, SQL, Python, Power BI, Tableau, Power Platform, or equivalent.
  • Ability to execute projects and communicate, manage stakeholders, and solve problems effectively.
  • Ability to work effectively across GQ Ops, IE, Planning, Process Engineering, Automation, IT, Facilities, vendors, and global teams.

Responsibilities

  • Contribute to the GQ Ops automation transformation roadmap by identifying and implementing opportunities to reduce manual effort, improve quality and safety, enhance productivity, and strengthen operational consistency.
  • Survey, benchmark, and evaluate industry solutions, and translate suitable technologies into practical recommendations for a future-ready, scalable, and highly automated GQ Ops reliability lab.
  • Develop and implement equipment and process automation solutions, including laser mark automation, ALU, robotics, vision systems, workflow digitization, and other manual-touch reduction opportunities.
  • Partner with operations teams to define automation requirements, perform ROI analysis, support vendor technical specifications, and execute FAT/SAT/PAC buyoff activities.
  • Apply common standards and best-known methods across sites based on prototype learning and operational requirements.
  • Support AMHS integration to improve material movement, throughput, system reliability, and operational execution.
  • Serve as a technical point of contact for GQ Ops lab automation and AMHS activities.
  • Collaborate with IT, Automation, Process, Planning, and Operations teams to resolve system issues, improve uptime, and strengthen system performance.
  • Support AMHS hardware solutioning, layout optimization, tool-interface readiness, testing, and operational integration for future GQ Ops automation deployment.
  • Develop, maintain, and improve reliable, automated, and scalable planning systems.
  • Develop and maintain IE models for equipment capacity, PeakUtil%, throughput, cycle time, bottleneck analysis, and future ramp readiness.
  • Translate lab ramp, product loading, tool availability, and process-flow assumptions into practical capacity models and planning scenarios that support leadership decision-making.
  • Improve planning-tool adoption, model accuracy, data quality, and system performance across GQ Ops.
  • Translate operational needs into practical digital tools, dashboards, reports, and decision-support systems.
  • Collaborate with Planning and Operations teams to bridge the Plan-to-Performance gap through data analysis, structured feedback, and robust modeling.
  • Explore and implement practical AI/ML or advanced analytics use cases to improve planning accuracy, prediction, automation, and decision-making capability.
  • Support MSH greenfield reliability lab enablement by translating business ramp needs into future-ready layout, process flow, automation-readiness, and operational execution requirements.
  • Perform layout planning, total utility metric analysis, equipment evaluation, infrastructure-readiness tracking, and tool ODD alignment to support the HBM reliability lab ramp and long-term capacity needs.
  • Coordinate with GEL, Process Engineering, Planning, Facilities, Automation, and vendors on equipment requirements, utility readiness, installation priorities, tool readiness, and process-equivalency timelines.
  • Incorporate automation, AMHS, tool-interface requirements, and data-driven planning considerations early in lab design to reduce rework and improve scalability.
  • Contribute as a technical member of the GQ Ops central team and take ownership of assigned engineering deliverables.
  • Plan and execute automation, modeling, and system-improvement projects in alignment with agreed priorities, scope, and timelines.
  • Communicate automation impact, model outputs, system risks, technical findings, and improvement recommendations clearly to working teams and leadership.
  • Collaborate across sites to standardize best-known methods, transfer prototype learning, and scale proven automation solutions across GQ Ops.
  • Demonstrate innovation, accountability, continuous improvement, and data-driven problem-solving in daily work.
  • Integrate AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness while exercising sound judgment and complying with organizational standards and legal requirements.
  • Contribute to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within the scope of work.

Desired Qualifications

  • Experience in semiconductor manufacturing, backend operations, reliability lab operations, automation deployment, or high-volume manufacturing.
  • Experience with robotics, AMHS, vision systems, auto-dispatching, workflow automation, or equipment integration.
  • Familiarity with automation protocols or standards such as SECS/GEM, E84, E87, or related factory automation interfaces.
  • Experience with ROI analysis, vendor technical specification review, FAT/SAT/PAC buyoff, and automation readiness assessment.
  • Exposure to Industry 4.0, AI/ML analytics, low-code automation, digital transformation, or smart manufacturing initiatives.
  • Ability to independently own technical deliverables, collaborate across functions, and share knowledge with team members.

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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