Subject Matter Expert - Automation & Ai/ml

Apple Apple · Big Tech · Shenzhen, Guangdong, China +1 · Operations and Supply Chain

This role focuses on leading the automation of manufacturing processes, specifically PVD coatings, by integrating robotics, PLCs, and machine learning/AI models for defect detection, predictive maintenance, and yield optimization. It requires a blend of physical automation leadership, digital transformation, and domain expertise in PVD processes and failure analysis.

What you'd actually do

  1. Lead the physical and digital automation of next-generation manufacturing processes for Apple’s world-class enclosure designs, focusing specifically on PVD coatings.
  2. Drive the deployment of advanced robotics and equipment hardware while leveraging massive data sets to train AI and machine learning models that detect defects, predict maintenance, and optimize production yields.
  3. Participate on a team tasked with developing and implementing next-generation automated processes for cosmetic and protective finishes, specifically focusing on PVD coatings and Ink Printing for Apple’s world-class enclosure designs.
  4. Lead the digital transformation of the coating process. Implement comprehensive data logging, traceability requirements, and machine vision systems.
  5. Leverage massive data sets to train and deploy machine learning/AI models that predict equipment maintenance, detect defects, and optimize process yield.

Skills

Required

  • BS/MS in Engineering (Automation, Mechatronics, Robotics, Computer Science, or equivalent cross-disciplinary degree)
  • 5+ years of professional experience working on automation, robotics, and data-driven applications in a high-volume manufacturing environment
  • Hands-on proficiency programming six-axis robots or major PLCs/IPCs
  • coding experience (Python, C++, Matlab) to deploy machine learning and vision solutions on the factory floor
  • Familiarity with surface treatments (e.g., PVD, CVD)
  • proven ability to conduct root-cause failure analysis on manufacturing defects to drive actionable automation improvements
  • Verbal and written English proficiency

Nice to have

  • Advanced statistical analysis skills and design/process optimization using DOE, Cpk, correlation, and GR&R (familiarity with JMP, Minitab, or Matlab)
  • Cross-disciplinary knowledge in Materials Science, Physics, or Chemistry
  • Deep understanding of PVD chamber hardware design, modification, and maintenance
  • strong track record of optimizing PVD process recipes for advanced cosmetic or functional coatings
  • Experience utilizing advanced measurement and characterization technologies (SEM, TEM, EDX, optical simulation software like Macleod, TFCALC) to drive complex root cause analysis and predictive quality modeling
  • Proficiency with CAD to review and design mechanical components/fixtures and create proper engineering part drawings using GD&T practices
  • Ability to program-manage across multiple projects, vendors, and resources globally

What the JD emphasized

  • masssive data sets to train AI and machine learning models
  • train and deploy machine learning/AI models
  • coding experience (Python, C++, Matlab) to deploy machine learning and vision solutions

Other signals

  • train AI and machine learning models that detect defects, predict maintenance, and optimize production yields
  • Leverage massive data sets to train and deploy machine learning/AI models that predict equipment maintenance, detect defects, and optimize process yield
  • coding experience (Python, C++, Matlab) to deploy machine learning and vision solutions on the factory floor