Manufacturing Quality Engineering Intern, Brittles
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 16, 2026. Apple scores B on the Alion truth index.
If you are the kind of students who are passionate on pursuing excellence, embracing challenges, enjoying work with others, learning new things along the way, Apple is the right place for you!
Apple Brittles Manufacturing Quality Engineering team (MQE) overall manage almost all the product/material quality in iPhone, iPad, Watch, Mac or any small parts that are made from glass, ceramic, sapphire or any brittle material. We closely work together with Apple PD, ID and our vendors to enable the fantastic design into reality product with statistic and systematic methodology in quality control and innovation in AIML application in mass production.
Description
Apple MQE is responsible for developing, applying and maintaining quality standards for materials, processes and products, solving quality engineering problems in creative and effective way.
- Dashboard/quality tool development using Tableau or Python
- Use machine learning/deep learning model/Data mining to train the AOI and reduce the mis-judgment rate
- Work with projects MQE to qualify and roll in inspection machines into mass production
- Explain and present AIML analysis and technical model to broad technical audience
Minimum Qualifications
Master or above, Mechanical Engineering & Automation/Computer Science/Industry Design/Applied Mathematics/Optics and Fine Mechanics or equivalent major is preferred
Excellent written and oral English communication skills
Intern Duration 3~6 months full-time
Working Location: Changsha/Shenzhen
90% business travel at suppliers' factories
Preferred Qualifications
Clear and logical thinking
Experienced in Python, Tableau for dashboard/analysis tool development would be preferred
Fundamental knowledge on computer vision / machine learning techniques to build models that are deployable into a manufacturing environment(AOI) with some time in project management
Technical skills in Machine or Computer Vision as well Machine Learning(CNN, transformer, Object detection/Image classification..)
Familiar with mechanical metrology system evaluation process, such as GRR, Correlation, Stability and Reliability