CapEx Supplier Quality Engineer (SQE)
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.
Minimum Qualifications
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.
Preferred Qualifications
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.