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