Core Technology Quality Engineers are responsible for driving quality improvement actions on future products. They enable a mass production capable manufacturing processes and develop plans to validate / verify new product quality at each development landmark. They approach problems in an engineering method and make data driven decision. Quality Engineers also bring up capable suppliers that can execute at a high level on an ongoing basis. This role requires an engineering mentality paired with data fluency and applied AI experimentation. Youll leverage Python for analysis use Tableau to visualize key performance indicators and build text-driven workflows that help engineers interpret act on and communicate quality data more is a Quality Engineering role first with AI as a force multiplier. You wont be developing AI models from scratch youll be integrating them into real-world factory workflows to scale Apples quality systems with clarity speed and measurable impact.
Bachelors in Mechanical Electrical Materials Science Industrial Engineering or a related field
5 years of proven experience in high-volume manufacturing quality engineering or development of consumer electronics or components
MS or PhD in Mechanical Electrical Materials Science or Industrial Engineering or equivalent
Experience using Python for engineering analysis and workflow automation
Familiarity with Data visualization tools such as Tableau or Power BI
Prompt design for AI-assisted workflows aimed at summarizing technical information
Experience working with SPC data image inspection logs defect classification or reliability metrics
Ability to partner with engineering operations and software teams
Excellent communication and structured problem-solving skills
Familiarity with manufacturing processes for components such as cameras optics haptics inductive elements or connectors
Exposure to computer vision models or manufacturing image data
Familiarity with agentic AI frameworks and applied prompt engineering for operational tools.
Passion for real-world AI applications that enhance quality speed and scalability
Experience with reliability modeling DOE and quality systems
Interest in integrating AI-powered assistants into engineering workflows
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