Core Technologies Quality Engineer

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.","responsibilities":"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%

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

Minimum Qualifications

Bachelors in Mechanical, Electrical, Materials Science, Industrial Engineering or a related field