Staff Machine Learning Engineer - Ads Auction

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass.

Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone.

We are seeking a self-motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace.

The ideal candidate has a strong background in auction theory, applied machine learning, and large-scale systems, along with hands-on experience building and optimizing auction-based ad delivery systems in production. You will have an excellent understanding of scalable architectures and thrive working in Agile environments.

Description

In this role, you are responsible for designing the core auction system that powers our advertising platform to drive optimal outcomes for advertisers, users, and our platform. You will have the opportunity to build the next generation solutions for marketplace optimization that enable driving optimal value for multiple stakeholders in the system. You will have the opportunity to apply your ability to move the state of the art techniques in a fast growing business that positively impacts publishers, developers and Apple users at global scale. The ability to be a great teammate under tight deadline constraints is key to success.

Minimum Qualifications

8+ years of experience working in online advertising, marketplace design, or large-scale recommendation/auction systems Strong background in auction theory, mechanism design, optimization, statistics, or machine learning. Ability to apply and implement research concepts, ultimately in production quality code Experience defining clear, testable research hypotheses, including intended impact on the business Deep knowledge of design of experiments, online experimentation approaches, preferably at scale Ability to formulate and advocate for R&D objectives and results to cross-functional team members including executive business leadership and product management Experience contributing and/or reviewing research for top conferences and publications Deep fluency in Java or Python. Experience with Spark, Hadoop or other distributed frameworks. Masters in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry.

Preferred Qualifications

Experience in ads optimization, recommendations, or search relevance optimization is highly preferred PhD in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning