Senior ML Engineer - Client Experimentation

Summary

At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in the App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

Ads ML Experimentation team is looking for a Senior ML Engineer to build the next generation of software platforms and systems to advance experimentation that connect millions of global users to content from publishers and developers. Your work will drive the experimentation framework development of machine learned algorithms at scale. You will build sophisticated systems essential in the end-end development of predictive algorithms. You will design and engineer tools for managing AB test experiments, for performing exploratory analysis, and for real-time monitoring of experiment behavior, while preserving privacy of our customers.

Description

Partner with business leaders and stakeholders to design, implement and evolve the features of a multivariate experimentation platform. Extend the experimentation platform to the client edge enabling safe execution and measurement of experiments on-device. Promote experimentation best practices across the organization. Execute on the experimentation roadmap and future integrations with data-driven prioritization. Exercise strong judgment and make thoughtful decisions with ambiguous situations. Striking the right balance between short-term wins vs. long-term success based on various constraints.

You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers and Apple.

Minimum Qualifications

• Strong experience in Experimentation frameworks, A/B testing and Machine Learning methodologies
• Familiarity with statistics and ability to use data analysis techniques to understand data quality, relationships between business metrics and technical performance
• Experience building client-side experimentation including SDK-based feature flagging, remote configuration and on-device experiment assignment (deterministic bucketing/consistent hashing) on iOS or comparable native platforms
• Proven track record instrumenting client-side exposure and metric logging (trigger-based exposure events, telemetry pipelines from device to backend) and reasoning about their correctness under real-world network and lifecycle conditions
• Hands-on experience operating staged/phased rollouts, holdbacks, kill-switches and forced-treatment overrides for client features, including safe ramp-up and fast rollback
• Fluency in programming languages like Java, Scala, Python and SQL
• Excellent communication, social and presentation skills
• Degree in Computer Science, Statistics, Applied Math or related field.
• 10+ years of industry experience designing, building, maintaining, and extending web-scale production systems.

Preferred Qualifications

• Familiarity with privacy-preserving client-side measurement (on-device aggregation, differential privacy, minimizing data leaving the device)
• Experience designing experiments on native UI/UX and app features
• Experience ensuring client/server allocation consistency, app-release cadence vs. server-controlled config, backward/forward compatibility across app versions, offline behavior, config caching and cold-start
• Prior experience in advertising industry
• 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
• Familiarity with ML applications in Ads, recommender systems, information retrieval or related domains.