ML Engineer - Experimentation, Portal

ML Engineer - Experimentation, Portal

At Apple, we believe in the power of technology to enrich people's lives. Everything we build is designed to empower people, including our advertising platform. We deliver ads in a way that benefits both customers and advertisers—helping people discover content, supporting creators, and protecting and respecting everyone's privacy. Our technology makes advertising possible on the App Store, Apple News, Stocks, and Apple TV. Everything we do is with the unwavering commitment to privacy you expect from Apple. Because when advertising is done right, it benefits everyone. The Ads ML Experimentation team is looking for a ML Engineer to help shape the future of how Apple's advertising systems experiment to connect millions of global users to content from publishers and developers. You'll build intuitive interfaces that transform complex statistical concepts and ML workflows into seamless user experiences, making advanced experimentation and AI accessible to teams across Apple Ads. This role requires partnering with cross-functional teams to effectively coordinate the complex interdependencies inherent in application development. A successful candidate has strong technical skills and is eager to create intuitive user experiences; they have a keen eye for the details that surprise and delight our customers.

In this role, you will design and build the next generation experimentation platform for the Apple Ads ecosystem. You will introduce AI-powered interfaces to introduce new insights, develop seamless workflows from model training to A/B testing and evaluation, all while delivering on Apple's privacy commitments. You will build complex large-scale and distributed software systems in cloud computing environments. You'll join a team where we obsess over user experience and believe the best interfaces make complex technology feel simple. You'll conduct user research, iterate on designs based on real feedback, and measure success through user adoption and satisfaction. We value technical excellence in service of user needs, not complexity for its own sake. You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. Some technologies you'll use: Infrastructure: Docker, AWS, Splunk, DataDog, etc. Frontend: Modern JavaScript/TypeScript, React, data visualization libraries (D3.js, Chart.js). Backend: Java 21, Spring Boot, Python, PostgreSQL.

Minimum qualifications:

• 2-3 years of experience in full-stack and ML model development with an in-depth understanding of data structures and algorithms. Industry internship experience is preferred.
• Experience with full-stack software development and design using React, Storybook, Java, Spring, Scala, Python.
• Building and deploying Machine Learning models to production using data processing tools including Spark.
• Working on A/B Testing infrastructure and/or methodologies using experience with multi-variate experimentation, and metrics generation/measurement.
• Experience with database design and database languages (SQL) to build applications.
• Using alerting and observability tools, including DataDog or Splunk, to monitor systems in production.
• Optimizing system performance using data structures and algorithms.
• Skilled at operating in a cross-functional organization.
• Ability to condense complex concepts and analysis into clear and concise takeaways that drive action.
• Curious business attitude with a proven ability to seek projects with a sense of ownership.
• Excellent communication, social and presentation skills.
• Desire to work in a fast-paced and challenging work environment.

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.