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Description
In this role, you will lead the physical and digital automation of next-generation manufacturing processes for Apple’s world-class enclosure designs, focusing specifically on PVD coatings. You will 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.","responsibilities":"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.
Physical Automation Leadership: Drive automation activities for key coating manufacturing processes. Work onsite with integrators to execute proofs of concept, review control logic and programming (Robotics/PLCs), define equipment hardware specifications, and provide onsite technical support at FAT/SAT to ensure equipment capability and productivity.
Digital Automation & AI/ML Enablement: Lead the digital transformation of the coating process. Implement comprehensive data logging, traceability requirements, and machine vision systems. Leverage massive data sets to train and deploy machine learning/AI models that predict equipment maintenance, detect defects, and optimize process yield.
Domain Integration & PVD Process: Understand the complex relationship between equipment automation parameters, PVD chamber hardware (e.g., vacuum systems, target configurations, gas delivery), and the underlying PVD process and materials chemistry (thin film stack design, formulation, sputtering power, coating, and curing processes).
Failure Analysis (FA) & Yield Improvement: Leverage deep Failure Analysis (FA) capabilities to troubleshoot production problems and close yield gaps. Correlate FA findings with equipment data to develop automated error-proofing and closed-loop process controls.
Work with cross-functional operations teams (PD, MD, ID) and contract manufacturers to evaluate implementation risk, create technical requirements/RFP packages, assess the capabilities of automation integrators, and provide DFM feedback.
Coordinate activities with global counterparts to push process capability. Present detailed technical and statistical analyses of manufacturing capability to diverse cross-functional teams and key decision-makers.
Preferred Qualifications
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 to effectively collaborate with Ink and PVD material SMEs.
PVD Process and Hardware Expertise: Deep understanding of PVD chamber hardware design, modification, and maintenance, coupled with a strong track record of optimizing PVD process recipes for advanced cosmetic or functional coatings.
FA Capabilities: 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.
Frequent domestic and some overseas travel expected.
Minimum Qualifications
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.
Physical & Digital Automation Experience: Hands-on proficiency programming six-axis robots or major PLCs/IPCs, combined with coding experience (Python, C++, Matlab) to deploy machine learning and vision solutions on the factory floor.
PVD & Failure Analysis Experience: Familiarity with surface treatments (e.g., PVD, CVD) combined with the proven ability to conduct root-cause failure analysis on manufacturing defects to drive actionable automation improvements.
Verbal and written English proficiency.
