Staff Machine Learning Engineer - Matching, Apple Ads

Apple•Cupertino, CA

About The Position

Apple Ads helps people find what they are looking for while helping advertisers grow their businesses. Its technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass, with an emphasis on user privacy and thoughtful integration into the experience. The Staff Machine Learning Engineer will develop algorithms for Apple Ads’ matching and retrieval systems, which retrieve relevant and engaging ads for users. The role focuses on building the next generation of retrieval systems to support business growth and improve platform revenue and ad quality. The engineer will own the end-to-end ideation, development, testing, and productization of algorithms, and will formulate approaches to greenfield product opportunities. The position involves solving complex ad-retrieval problems while adhering to Apple’s privacy principles, applying research concepts in production-quality code, and collaborating with product management, business leadership, and cross-functional teams. The engineer will help set an innovation roadmap, assess the feasibility and robustness of new capabilities, conduct large-scale experiments, review and contribute to research, and present findings across the organization.

Requirements

At least 7 years of experience building machine-learning capabilities across multiple product areas at scale.
Proven experience in natural language processing (NLP), information retrieval, and search.
Ability to apply and implement research concepts in production-quality code.
Experience defining clear, testable research hypotheses, including 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 or equivalent experience with large data science or machine-learning projects in industry.
A Ph.D. or equivalent experience in NLP, machine learning, deep learning, large language models, reinforcement learning, or a related field, together with experience building production systems or equivalent experience with large data science or machine-learning projects in industry.
Excellent understanding of scalable architectures.
Ability to work effectively as a team player under tight deadlines and in Agile environments.

Nice To Haves

Experience developing and implementing machine-learning algorithms in the ads space.

Responsibilities

Develop machine-learning algorithms for Apple Ads’ matching and retrieval systems.
Own the end-to-end ideation, development, testing, and productization of algorithms.
Improve platform outcomes, revenue, and ad quality, and develop approaches to greenfield product opportunities.
Apply advanced techniques and algorithms to improve the ad network and deliver differentiated product capabilities.
Work with product management and business leadership to prioritize an innovation roadmap across technical domains.
Define clear, testable research hypotheses, including their intended business impact.
Design and conduct large-scale and complex experiments to understand the effects of changes.
Apply research concepts in production-quality code and contribute to or review research for leading conferences and publications.
Collaborate with cross-functional teams to ensure new capabilities are feasible and robust, while adhering to Apple’s privacy principles.
Present findings across the organization.