About The Position

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, Maps, 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. When advertising is done right, it benefits everyone. Apple's advertising platform connects millions of developers and businesses with users across one of the world's most valuable digital ecosystems -- and the intelligence behind every ad decision lives in the algorithms. As the Director of Algorithms within Ads Engineering, you will lead the applied scientists and ML engineers who build and scale that intelligence: state-of-the-art retrieval, ranking, auction, and budget optimization systems that determine relevance, efficiency, and outcomes at massive scale. This is a role for a leader who wants to solve hard algorithmic problems that matter -- where privacy constraints sharpen the work rather than limit it, and where craft and rigor are the standard. As the Director of Algorithms within Ads Engineering, you will be the driving force behind the intelligence engine that powers Apple's advertising ecosystem. You will lead a multidisciplinary organization of engineering managers, applied scientists, ML engineers, and systems engineers -- setting the vision, shaping the roadmap, and delivering at the intersection of cutting-edge research and production-scale engineering. Success in this role requires a leader who approaches problem-solving with tact, values diverse perspectives, and builds strong, trusting partnerships across organizational boundaries to deliver solutions that respect our users and empower our advertisers.

Requirements

  • 15+ years of professional experience in Machine Learning, Applied Science, or Software Engineering, with a strong focus on performance advertising, search, or recommendation systems.
  • 10+ years of engineering leadership experience, including a proven track record of managing other managers as well as senior/staff-level individual contributors.
  • Deep technical expertise across the entire algorithms funnel, including signals processing, candidate matching, predictive modeling (e.g., CTR/CVR), and ranking.
  • Experience with modern techniques using embeddings, transformer architectures, distillation methods, and reinforcement learning based methods.
  • Extensive experience in algorithm engineering, with a strong understanding of how to build, deploy, and scale high-throughput, low-latency ML systems in production environments.
  • Exceptional communication and diplomatic skills, with the ability to build consensus, navigate complex cross-functional relationships, and articulate technical strategies to both technical and non-technical stakeholders.
  • A demonstrated commitment to fostering an inclusive, respectful, and highly collaborative team culture that empowers individuals to do their best work.
  • Strong alignment with Apple's core values, particularly regarding user privacy and delivering premium user experiences.

Nice To Haves

  • Experience with privacy-enhancing technologies (PETs) or building ML systems under strict privacy constraints.
  • Experience with Ads technology and domain.
  • Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field, accompanied by relevant industry experience.

Responsibilities

  • Lead the applied scientists and ML engineers who build and scale intelligence for Apple Ads.
  • Build and scale state-of-the-art retrieval, ranking, auction, and budget optimization systems.
  • Determine relevance, efficiency, and outcomes at massive scale.
  • Lead a multidisciplinary organization of engineering managers, applied scientists, ML engineers, and systems engineers.
  • Set the vision, shape the roadmap, and deliver at the intersection of cutting-edge research and production-scale engineering.
  • Approach problem-solving with tact.
  • Value diverse perspectives.
  • Build strong, trusting partnerships across organizational boundaries.
  • Deliver solutions that respect users and empower advertisers.
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