The role of Machine Learning Engineering Manager at Apple focuses on building the next generation advertiser recommendation engine to optimize campaign performance on Apple Ads. The team is responsible for driving innovation in Ads Recommendations, leveraging advanced machine learning techniques and innovative technologies. This position requires collaboration with cross-functional partners to develop strategies and deliver scalable solutions. The manager will lead a talented team, shaping the technical direction and ensuring the reliability of the systems.

• 8+ years of experience in machine learning, statistics, and quantitative optimization.
• At least 2-3 years of experience as a tech lead or at least 1 year as an engineering manager.
• Deep understanding of modern machine learning techniques, statistics, and quantitative optimization.
• Experience working with operational teams on deployment, monitoring, and system management.
• Experience running A/B tests and pilots for sales or advertiser-facing applications.
• Hands-on experience with Python or Java in a production environment.
• Proficiency in databases, SQL, and scripting languages for data processing and model deployment.
• BS, or equivalent experience, in AI, ML, Mathematics, Computer Science, or a related field.
• 5+ years of experience leading teams that apply advanced statistical or ML methods.
• Previous experience in the online advertising domain is a big plus.
• MS/PhD, or equivalent experience, in AI, ML, Mathematics, Computer Science, or a related field.

• Define and implement the technical strategy for building the next generation recommendation engine.
• Leverage innovative research and technology including the latest GenAI and agentic approaches.
• Shape the strategy and roadmap for allied areas like campaign optimization and auction optimization.
• Design and analyze sophisticated algorithms to deliver incremental improvements that are privacy compliant.
• Execute and analyze A/B tests and pilots to drive continuous improvements in advertiser-facing applications.
• Work closely with engineering and business teams to scale innovations.
• Ensure efficient and reliable model deployment and execution.
• Architect and scale intelligence systems, addressing operational concerns and performance optimizations.
• Lead, mentor, and grow a talented team of engineers.

• 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.