About The Position
This role focuses on customized equipment quality management for sophisticated equipment in a high-volume global manufacturing landscape. As a key member of the cross-functional team, you will oversee quality and reliability of equipment from multiple suppliers, ensuring seamless alignment with quality and operational standards. As a CapEx Supplier Quality Engineer within Product Operations organization, you will own the quality lifecycle of customized capital equipment - assembly automation, robotics, vision/metrology systems, and precision tooling - that produces Apple"s products at global scale. You will be working with strategic equipment suppliers and Contract Manufacturers, along with cross-functional teams to ensure every equipment meets Apple"s standards from FAT through MP ramp.
Requirements
- Bachelor"s Degree (or equivalent) in Mechanical, Electrical, Automation, Mechatronics, Industrial, or related Engineering discipline.
- 4+ years of supplier quality, equipment engineering, or manufacturing engineering experience in high-volume electronics, semiconductor, automotive, or precision-mechanical industries.
- Proven hands-on experience with customized capital equipment for the 3C industry (Computer, Communication, Consumer Electronics) or high-precision components — robots, vision systems, automated assembly lines.
- Working knowledge of ISO 9001 and equipment qualification protocols: IQ/OQ/PQ, FAT/SAT, MSA, GR&R.
- Hands-on competency with core quality tools: DFMEA/PFMEA, 8D, Root Cause Analysis, Cpk, Control Plans, DOE.
- Strong adaptability to navigate ambiguous scenarios and dynamic project demands across multiple parallel programs.
- Exceptional conflict resolution and interpersonal skills to drive alignment across Apple cross-functional teams and global suppliers.
Nice To Haves
- Master"s degree in Engineering or Quality Management.
- Ability to read and interpret mechanical and electrical drawings, GD&T, PLC/HMI logic, and detailed equipment specifications.
- Quality management experience in customized manufacturing or capital-equipment supply chains.
- Experience with large-scale data analysis, scripting (Python/SQL), and applied machine learning for manufacturing analytics.
- Track record of leveraging AI and emerging technologies — computer vision, AOI, predictive maintenance, digital twins, generative AI — to enhance work efficiency and quality processes.
Responsibilities
- Partner with equipment suppliers and Apple's Engineering teams to align on quality control specifications and requirements, assess supplier capability (process capability, and quality maturity), and validate readiness for Mass Production (MP) roll-out.
- Define and execute the Equipment Quality Plan through Design for Manufacturability (DFM) reviews, FAT/SAT protocols, and Standard Operating Procedure (SOP) development for new features and programs.
- Oversee supplier factory preparations, in-process quality control, and intensive outgoing inspections during new program design, validation, and production ramp-up.
- Lead First Article Inspection (FAI) and equipment qualification activities at supplier sites.
- Drive vendor performance through a structured scorecard system covering quality, delivery, responsiveness, and cost-of-poor-quality metrics, with cadenced business reviews.
- Update equipment quality control criteria based on Engineering Change Orders (ECOs) and field/line learnings.
- Partner with TechOps Failure Analysis & Corrective Action (FACA) teams to drive 8D closure on equipment-related quality escapes.
- Provide clear, concise reports on supplier readiness and critical quality/compliance issues to stakeholders and executive management.
- Support new vendors in establishing and implementing QMS, with ongoing monitoring of execution and maturity.
- Coach vendors to produce accurate, timely quality and compliance reports and to sustain a culture of continuous improvement.
- Drive automation of supplier Quality Management Systems (QMS) using new technologies, integrating customized quality control criteria into standardized, scalable processes.
- Champion AI/ML-based anomaly detection, automated reporting pipelines, and digital traceability across the supplier ecosystem.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
