Staff Machine Learning Engineer - Matching, Apple Ads

Apple•Cupertino, CA

About The Position

Apple Ads is seeking a Staff Machine Learning Engineer to develop algorithms for its advertising retrieval system. Matching is a critical part of the Ads funnel, responsible for retrieving relevant and engaging ads. The role will help build next-generation retrieval systems to support future business growth, improve platform revenue and ad quality, and explore greenfield product opportunities. The engineer will own the end-to-end ideation, development, testing, and productization of retrieval algorithms. The work involves complex problems in ads retrieval, applying research concepts in production-quality code, and ensuring solutions adhere to Apple’s privacy principles. The role also includes reviewing and contributing to research, collaborating with cross-functional and organizational partners to deliver robust capabilities, and presenting findings across the organization. More broadly, the position develops machine learning models and production recommendations, conducts large-scale experiments, and partners with business stakeholders on products and an innovation roadmap. It calls for leadership in developing advanced techniques and algorithms for the ad network, a strong understanding of scalable architectures, and the ability to work effectively in Agile environments and under tight deadlines.

Requirements

7+ years of experience building machine learning capabilities across multiple product areas at scale.
Proven experience in natural language processing, information retrieval, and search.
Ability to apply and implement research concepts in production-quality code.
Experience defining clear, testable research hypotheses, including their intended business impact.
Deep understanding of experimental design and online experimentation approaches, preferably at scale.
Experience contributing to and/or reviewing research for top conferences and publications.
A master's degree, or equivalent experience, in NLP, machine learning, statistics, forecasting, optimization, reinforcement learning, or a related field, together with experience building production systems; alternatively, equivalent experience working on large data science or machine learning projects in industry.
Excellent understanding of scalable architectures.
Ability to work effectively in Agile environments and as a team player under tight deadline constraints.

Nice To Haves

PhD, or equivalent experience, in NLP, machine learning, deep learning, large language models, reinforcement learning, or a related field, with experience building production systems or equivalent experience working on large data science or machine learning projects in industry.
Experience developing and implementing machine learning algorithms in the advertising space.

Responsibilities

Develop machine learning algorithms for Apple Ads' retrieval system.
Own the end-to-end ideation, development, testing, and productization of retrieval algorithms.
Drive improvements in advertising outcomes, platform revenue, and ad quality, and formulate approaches for greenfield product opportunities.
Apply research concepts and implement them in production-quality code.
Design clear, testable research hypotheses and connect them to intended business impact.
Conduct and contribute to large-scale and complex experiments to evaluate effects and outcomes.
Ensure solutions adhere to Apple's privacy principles.
Review and contribute to state-of-the-art research.
Collaborate with cross-functional teams and organizational partners to ensure new capabilities are feasible and robust.
Work with product management and business leadership to prioritize an innovation roadmap across technical domains.
Present findings across the organization.
Lead development and application of advanced techniques and algorithms that improve the ad network.