Senior Machine Learning Scientist - Ad Campaign Optimization

Socket.dev; Cupertino (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Apple is seeking a highly motivated engineer to design and build scalable machine learning and optimization capabilities for Apple Ads. You will help advertisers optimize campaigns, drive performance, and push state-of-the-art techniques into production at a global scale.

The role requires deep ML knowledge, strong programming in Java or Python, and experience with distributed frameworks like Spark/Hadoop. Collaboration with cross-functional teams under tight deadlines is essential.

Qualifications

• 5+ years building ML and quantitative optimization at scale.
• Experience in ML, quantitative methods, control systems, or reinforcement learning.
• Translate research concepts into production-quality code.
• Define testable hypotheses with impact on the business.
• Strong knowledge of online experimentation at scale.
• Present R&D results to cross-functional leadership and product teams.
• Contribute to research discussions for conferences/publications.
• Fluent in Java or Python.
• Experience with Spark, Hadoop or similar distributed frameworks.
• Masters/PhD with production ML experience or equivalent industry work.

Responsibilities

• Design and build scalable ML solutions for Apple Ads to optimize campaigns.
• Develop budget and bid optimization features to improve performance.
• Move state-of-the-art techniques into production at global scale.
• Collaborate with cross-functional teams under tight deadlines.

Skills

Machine learning

Optimization

Data analysis

Java

Python

Education

Master's degree in ML/Statistics/Control

PhD in ML/Statistics/Optimization

Tools

Spark

Hadoop

Job description

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

• 5+ 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
• Masters 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
• 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