The role involves building the next generation of Apple Ads platforms to enhance the advertising experience for users and advertisers. The team focuses on developing machine learning and optimization algorithms to ensure high-quality ad placements while maintaining a healthy marketplace. Candidates should thrive in Agile environments and possess a strong understanding of scalable architectures. This position offers the opportunity to impact global advertising strategies positively.

• 8+ years of experience building machine learning and quantitative optimization capabilities at scale.
• Experience in machine learning, quantitative methods, control systems, or reinforcement learning.
• Deep fluency in Java or Python.
• Experience with Spark, Hadoop, or other distributed frameworks.
• PhD in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning, or related field, or equivalent industry experience.

• Design and build scalable solutions for advertisers to optimize their campaign goals.
• Develop budget and bid optimization strategies to enhance campaign performance.
• Implement research concepts into production quality code.
• Define clear, testable research hypotheses and assess their business impact.
• Advocate for R&D objectives and results to cross-functional teams, including executive leadership.

• 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.