Manufacturing Process Engineer II

PHOTRONICS INC•Boise, ID

17h•Onsite

About The Position

The IRP RDA Engineer is responsible for driving detection, classification, and reduction of all defect signals across the photomask manufacturing value stream—both traditional physical mask defects (e.g., extensions, intrusions, pattern defects) and non-physical defects such as flow breakdowns, missing or ineffective OCAP, aged holds, disposition delays, and other systemic constraints that impact quality, yield, and cycle time. This role owns the inspection–review–repair (IRP) workflow and leverages real-time defect analysis (RDA) to identify root causes, drive containment and corrective actions, and improve process capability. The engineer partners with lithography, metrology, equipment, manufacturing, and planning/operations stakeholders to ensure stable production performance through data-driven decision making and continuous improvement.

Requirements

Hands-on experience in photomask or semiconductor manufacturing environments, including working effectively in/with cleanroom operations.
Working knowledge of photolithography/patterning and how upstream process variation can manifest as downstream inspection, review, repair, or disposition signals.
Ability to transform high-volume, mixed-quality manufacturing data into actionable insights (paretos, excursion detection, defect taxonomy, signal quality metrics) and to communicate results clearly to stakeholders.
Strong fundamentals in structured problem solving and root cause (5-Why, fishbone, fault tree), including containment, corrective action, and verification of effectiveness.
Demonstrated ability to build, improve, and sustain OCAP/standard work (response plans, decision trees, escalation paths) with audit-ready documentation.
Working knowledge of SPC concepts (control charts, capability, common vs. special cause) and experimental methods (DOE), including measurement system considerations.
Proficiency with common analysis and visualization tools (e.g., Excel, Power BI, JMP) and comfort working with manufacturing databases or basic automation/scripting (SQL/Python preferred; equivalent experience acceptable).
Ability to lead cross-functional routines (defect pareto reviews, excursion reviews, aged-hold scrubs) and drive timely closure through influence, prioritization, and clear action tracking.
5+ years of experience in photomask manufacturing and/or semiconductor manufacturing (yield, process, equipment, or manufacturing engineering).
Experience in inspection/review/repair (IRP), defect review, yield learning, or nonconformance disposition workflows; photomask experience preferred.
Experience with SPC, data analysis, and root cause methodologies, including translating findings into control plans/OCAP updates.
Experience improving operational execution using data (e.g., aged-hold reduction, disposition cycle time, queue-time management, rework reduction) in partnership with manufacturing and planning/operations.
Experience with dashboarding, data extraction, and/or automation (e.g., Power BI, JMP, SQL, Python, Excel VBA) to enable near-real-time monitoring and action tracking.
Bachelor’s degree in Electrical Engineering, Materials Science, Physics, Chemical Engineering, or related field.

Responsibilities

Own and continuously improve the inspection–review–repair (IRP) workflow, ensuring fast, consistent disposition and effective closure of defect signals.
Integrate and analyze diverse defect signals (inspection hits, review outcomes, repair results, holds, rework, OCAP usage, queue time) to identify trends, paretos, and excursion drivers.
Develop and maintain real-time monitoring (RDA) systems and dashboards for defect health, containment status, and flow performance (e.g., holds aging, disposition cycle time, IRP queue health).
Lead root cause analysis and corrective/preventive actions for yield, quality, and flow excursions—spanning tool/process mechanisms, recipe/configuration, handling/contamination, and operational breakdowns.
Partner with inspection, review, and metrology teams to improve signal quality (sensitivity, nuisance reduction, classification accuracy) and to standardize defect taxonomy across tools and workflows.
Support rapid, high-quality dispositions by evaluating impact (printability where applicable), driving clear containment actions, and reducing time-to-decision for holds, rework, and IRP exceptions.
Support qualification and optimization of inspection, review, and repair tools, including recipe governance, matching, and sustaining plans tied to defect and flow performance.
Apply SPC, DOE, and statistical methods to improve both process robustness and workflow robustness (e.g., defect escape reduction, rework reduction, queue-time variation reduction).
Drive OCAP and standard work effectiveness: identify gaps, author or improve response plans, ensure ownership/closure, and verify sustained control through audit-ready evidence.
Own recurring defect/flow review routines (e.g., pareto reviews, aged-hold scrubs) and coordinate cross-functional actions to eliminate chronic constraints in the back end of the photomask manufacturing process.
Collaborate with process, equipment, manufacturing, and operations teams to improve yield, cycle time, and cost through prioritized, closed-loop problem solving.
Document defect mechanisms, control strategies, OCAP/standard work, and lessons learned; maintain clear knowledge bases that accelerate future disposition and root-cause efforts.