Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. The people here at Apple don’t just build products - they craft 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! At Apple, Quality is one of the cornerstones of what makes our products and technologies phenomenal. Our teams are responsible for ensuring our customers receive the high quality and reliability they expect. We are seeking a Quality Engineer with strong data fluency-skilled in Python, Tableau, and applied AI workflows-to help scale quality processes in high-complexity, high-volume manufacturing. This role bridges traditional quality engineering skills with emerging AI-driven workflows, ensuring factory intelligence is applied in the real world to deliver measurable improvements in speed, accuracy, and decision-making.

DESCRIPTION

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. You’ll 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 efficiently. This is a Quality Engineering role first, with AI as a force multiplier. You won’t be developing AI models from scratch - you’ll be integrating them into real-world factory workflows to scale Apple’s quality systems with clarity, speed, and measurable impact.

MINIMUM QUALIFICATIONS

• 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

PREFERRED QUALIFICATIONS

• 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

• Identify and drive quality improvement opportunities in future products
• Lead Process FMEAs on new technologies and manufacturing processes
• Conduct technical failure analysis to support root cause investigations
• Generate and implement Product Quality Plans (PQPs)
• Establish quality monitoring mechanisms and metrics across the supply chain
• Build and maintain Python-based tools for data automation, transformation, and visualization
• Create Tableau dashboards for trend detection, anomaly flagging, and performance tracking
• Apply prompt engineering to design AI-powered workflows for smart search, RCA lookup, report summarization, and supplier interaction
• Pilot and refine agentic AI workflows that support test correlation, post-build analysis, and issue triage
• Ensure data foundations (ownership, labeling, quality) are established and maintained for manufacturability and analysis
• Collaborate with the in-house software/ML Ops team to validate and iterate on AI and automation concepts
• Gather and synthesize user feedback to continuously improve tool usability and adoption
• Travel internationally up to 25%