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 theyre 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. nnEverything 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 sizesfrom small app developers to big global brands. Because when advertising is done right it benefits 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. nnThe 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.

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.

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. nYou 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 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. nYou will lead the conception development and delivery of state of the art capabilities that differentiate our products and are core to our business. nYou will work with a variety of cross functional business partners to set strategy and bring end-to-end solutions that scale as we grow.

8 years of experience working in online advertising marketplace design or large-scale recommendation/auction systemsnStrong background in auction theory mechanism design optimization statistics or machine to apply and implement research concepts ultimately in production quality codenExperience defining clear testable research hypotheses including intended impact on the businessnDeep knowledge of design of experiments online experimentation approaches preferably at scalenAbility to formulate and advocate for Ru0026D objectives and results to cross-functional team members including executive business leadership and product managementnExperience contributing and/or reviewing research for top conferences and publicationsnDeep fluency in Java or with Spark Hadoop or other distributed 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.

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