Machine Learning Scientist - Ads Auction

Weekly Hours : 40

Role Number : 200622428-0836

Summary

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!

Description

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.

You will be responsible for designing, analyzing, and optimizing the core auction system that powers our advertising platform, develop production code to generate high quality ad recommendations and work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You will drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network. You have, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You will lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business.

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. The ability to be a great teammate under tight deadline constraints is key to success.

Minimum Qualifications

5+ 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

BS in in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or 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

MS or PhD in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or equivalent experience working with large data science / machine learning projects in industry

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant () .