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Apple Manufacturing Quality Engineer - iPhone China, Guangdong Province, Shenzhen 792002122
18.11.2024
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Description
Key responsibilities will include: - You will partner with multi-functional teams to evaluate design and processes at the concept phase- Develop measurement technologies, control strategies, information systems, and manufacturing methods that achieve adventurous specifications at mass production scale - You will develop and implement groundbreaking quality inspection tools to evaluate cosmetic and dimensional part characteristics - Compile and evaluate data to determine appropriate limits and variables for process and part specifications - Lead activities to balance unparalleled quality with scalable yields - You will collaborate with internal and external groups to ensure that proper definition of quality expectations and that appropriate assurance techniques are used for the product - Evaluate and communicate yields of new and existing processes
Minimum Qualifications
- BS or equivalent experience in Mechanical Engineering, Industrial Engineering, Manufacturing Engineering, Industrial Technology, or similar
- Experience in manufacturing and quality control
- Experience developing process quality plans, supplier quality audits, and driving corrective actions and failure analysis efforts
Preferred Qualifications
- Working knowledge of mechanical quality and reliability concepts, supplier management, and general manufacturing operations
- Experience with the development and evaluation of measurement systems
- Project management experience and a deep understanding of problem solving tools including design of experiments, root cause analysis and statistical analytical tools
- Experience with any of the following: mechanical enclosures, castings, plastic parts, injection molding, tooling, jigs, fixtures, or automotive high volume quality manufacturing engineering
- Exceptional ability to establish relationships; data-driven and willing to take action; enthusiastic and motivated; and detailed while managing several work streams.
- Knowledge on Data Science, including Statistics, Machine Learning, Regression are preferred
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