This role at Apple involves collaborating with mechanical and quality engineers to integrate machine learning and computer vision into industrial applications. The team focuses on developing inspection equipment that ensures products meet Apple's high standards across various hardware. The position requires a strong background in machine learning, software development, and data analysis, with an emphasis on improving production processes. Candidates will also engage in international travel to manufacturing sites as part of their responsibilities.

• 12+ years of hands-on experience applying machine learning and/or computer vision techniques in industrial applications
• Strong software development skills with proficiency in Python
• Experience with machine learning and statistical-analysis libraries such as scikit-learn, PyTorch, and Keras
• Ability to explain and present analyses and machine learning concepts to a broad technical audience
• BS in a related engineering field

• Collaborate with mechanical and quality engineers to apply machine learning and computer vision to manufacturing situations
• Develop and deploy ML models for inspection equipment that judges millions of units per day
• Identify opportunities in production processes to apply machine learning tools for improvements
• Assemble and analyze large data sets through SQL-based querying or code development
• Develop software components in Python, Java, and/or C/C++/Obj-C for data automation systems

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.