Staff Machine Learning Engineer - Ads Bidding & Pacing

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. You should have

experience developing and implementing machine learning or optimization

algorithms, ideally within the ads space, recommendations, or search relevance.

You will have an excellent understanding of scalable architectures and thrive

working in Agile environments.

DESCRIPTION

In this role, you will

• design and build scalable solutions that enable
• advertisers to optimize for their campaign goals and performance on the Apple
• Ads. You will have the opportunity to build the next generation solutions for
• budget and bid optimization that enable driving optimal campaign performance and
• advertiser experience. 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 building machine learning and quantitative optimization
• capabilities across many different product areas at scale Experience in machine
• learning, quantitative methods, control systems, or reinforcement 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. PhD in 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