Apple is seeking a highly experienced and strategic Machine Learning Data Engineer to enhance machine learning data quality. This role involves transforming complex data challenges into scalable processes and high-fidelity datasets for innovative consumer products. The engineer will bridge technical tools, cross-functional teams, and regulatory compliance, focusing on maximizing model ROI through rigorous data quality. If you are passionate about data evaluation frameworks and leading initiatives, this position is for you.

• BS in Computer Science, Data Engineering, Data Science, Mathematics, or a related field, or equivalent industry experience.
• 10+ years of experience in data analysis or ML data operations.
• Experience in data analysis, data engineering, and machine learning data operations.
• Experience operating within global data privacy frameworks such as GDPR and CCPA.
• Proven background in leading complex, cross-functional programs focused on ML data quality.
• Excellent written and verbal communication skills.

• Transform ambiguous data challenges into scalable processes and clear policies.
• Act as a crucial link between technical tools, cross-functional teams, and regulatory compliance.
• Design data quality control processes and data curation workflows.
• Lead initiatives to maximize model ROI through rigorous data quality.
• Consult with diverse engineering stakeholders to gather requirements and explain complex models.

• 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.