QA Optimization Engineer
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Job Description
The Quality Optimization Engineer is responsible for identifying, analyzing, and eliminating manufacturing yield loss while ensuring operational capabilities align precisely with product specifications. Operating with a high degree of autonomy, this individual acts as a critical liaison between Operations, Quality, R&D;, and Engineering to clarify quality standards and reduce operational ambiguity.
The ideal candidate possesses exceptional critical thinking skills, a strong analytical mindset, and a proactive approach to cross-functional leadership. They leverage foundational engineering principles alongside modern technologies—including AI-driven data tools and predictive analytics—to drive sustainable yield improvements and optimize manufacturing processes.
Primary Responsibilities
• Yield & Loss Optimization: Lead investigative efforts to identify drivers of manufacturing loss, scrap, and downtime; design and execute corrective strategies to improve overall equipment effectiveness (OEE).
• Autonomous Problem Solving: Drive root-cause investigations from end-to-end utilizing formal methodologies (e.g., 8D, DMAIC, 5-Why, Fishbone Analysis) with minimal supervisory oversight.
• Standard Clarification & Operational Alignment: Partner directly with Operations leadership to clarify quality standards, establish unambiguous visual/measurable criteria, and ensure floor-level understanding to prevent operational losses.
• Specification & Capability Alignment: Assist in drafting, refining, and reviewing product specifications; evaluate current manufacturing process capabilities (Cpk/Ppk) to ensure new and existing specs are technically achievable on the production line.
• Cross-Functional Collaboration: Partner seamlessly across Production, Engineering, Maintenance, and R&D; to implement sustainable process controls without relying on top-down authority.
• Leverage Advanced & AI Tooling: Integrate artificial intelligence tools, machine learning applications, and modern data platforms to enhance data synthesis, predictive modeling, and root-cause discovery.
• Process Standardization: Translate problem-solving outcomes and specification updates into standard operating procedures (SOPs), control plans, and training materials to safeguard against defect recurrence.
• Metrics & Reporting: Generate and present quantitative performance metrics, capability studies, and project updates to plant and operations management.
• Quality Testing & Validation: Conduct targeted age testing on key product lines to validate long-term performance and reliability, integrating findings directly into problem-solving efforts and quality investigations.
Requirements
Department: Engineering Services
Function: Engineering
Experience Level: Associate