About The Position

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it. Operations engineering is engaged from the earliest stages of new product introduction (NPI) engineering builds, through ramp-up, and throughout the product lifecycle. The team ensures high quality and high yield by working with cross-functional teams to quickly resolve technical and operational issues, and by serving as an interface between vendors and downstream module integrators. We are seeking a Product Quality Engineer (PQE) to oversee the end-to-end quality process, from components to modules, based in Japan! Product Quality Engineer, as part of Technical Operations, will work in conjunction with the Manufacturing Process Engineering team as well as a multi-functional team of Design, Engineering, Sourcing, and Product Development Engineers to ensure top-quality products and services from suppliers and to drive excellence into everything we do. In this highly visible technical quality lead role, you will be the resident factory expert in manufacturing processes, yields, and overall factory readiness for mass production, combining your knowledge of displays and display-related components to deliver results on a tight timeline.

Requirements

  • End-to-end display/component quality management experience required
  • Proven experience in leveraging AI and machine learning for advanced data analysis and generating actionable insights
  • Understanding of, and skill and experience in, smart manufacturing AI tools
  • Hands-on experience in electrical, chemical, and optical analysis for display/component quality improvement
  • Fluency in English and Japanese is a mandatory requirement
  • BS or MS degree in Physics, Chemistry, Materials Science, or a related field
  • Strong interpersonal and communication skills, with the ability to concisely understand and communicate issues and lead cross-functional teams to solutions
  • Experience with external suppliers in program management
  • Background in displays, materials, and semiconductor processes
  • Knowledge of GenAI tool application
  • Knowledge of TFT, touch, electrical, and optical operations in display technology
  • In-depth experience in electrical and optical display failure analysis; knowledge of general analysis tools (e.g., FIB/SEM, CT, AFM, FTIR/Raman, spectrometer, TDR, etc.)

Responsibilities

  • Act as a lead engineer to drive overall quality system development and quality control tool development, ensuring the delivery of scalable products
  • Review product/process design documentation and specifications to ensure alignment with process capability and yield targets
  • Present timely, concise reports and plans regarding product yield performance and specification convergence status.
  • Drive failure analysis, corrective action implementation plans, and yield bridge to mass production
  • Review suppliers’ quality control flows, in-process quality control systems, and quality control plans for incoming components and outgoing products.
  • Identify shortfalls and corrective actions to ensure compliance with design and yield targets
  • Work with supplier process and quality teams to map out process development exercises, secure resources, and expedite FA to improve yields and meet schedules in line with program goals
  • Assess suppliers’ production readiness to support build events and production ramp-ups.
  • Identify potential execution issues and provide recommendations to mitigate risks
  • Ensure processes and suppliers are performing as expected during production ramps, addressing critical issues immediately
  • Monitor suppliers’ process performance and yield loss at different process nodes periodically to prevent quality issues
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