What are the responsibilities and job description for the Senior Machine Learning Engineering Manager - Ads Predictions position at Apple, Inc.?
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. \\n\\nOur 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 looking for a leader with deep experience in Ad Tech who has built and scaled complex machine learning models in production. Preferably, you have a strong track record of delivering high-impact response prediction systems (e.g., click-through rate, conversion rate, post-conversion optimization) at scale, and understand the nuances of optimizing for user engagement, relevance, and long-term value under latency constraints.\n\nYou bring hands-on experience developing and deploying large-scale models, with an appetite for pushing state-of-the-art techniques and advancing model capability through increased scale and complexity. You are motivated by privacy-preserving machine learning and have experience building systems that operate effectively within privacy-first constraints.\n\nIn this role, you will lead the strategy and development of inference models that predict and optimize user interactions with ads, working across the full modeling stack-from data and model training pipelines to real-time serving and experimentation. You will partner closely with engineering and product teams to define and execute a forward-looking roadmap. You thrive in a fast-paced, Agile environment and are a hands-on ML leader who can drive execution while building strong, collaborative teams.
10 years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data sets\nYou can actively participate in investigations into multiple streams of ads quality data, and draw conclusions from data, recommend actions\nYou have experience in some of the following domains: Algorithms, Architecture, Artificial Intelligence, Database Systems, Data Mining, Distributed Systems, Machine Learning, Networking, Statistics, Game Theory, Auction Design, or other experience with rigorous Quantitative Analysis or Systems Software implementation\nPractical understanding of the mathematics behind modern machine learning, linear algebra and statistics\nYou have experience developing and leading teams who develop in Python or Java\nYou are familiar with databases, SQL, and scripting languages\nProven ability to take requirements from design through to implementation both independently and with larger teams\nYou thrive working closely with operational teams on deployment, monitoring, and management concerns\nYou actively manage performance of the team reporting to you and take responsibility to drive its outcome\nPhD or MS in AI/ML/Mathematics/CS or related field
10 years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data setsPhD in AI/ML/Mathematics/CS or related field
We are looking for a leader with deep experience in Ad Tech who has built and scaled complex machine learning models in production. Preferably, you have a strong track record of delivering high-impact response prediction systems (e.g., click-through rate, conversion rate, post-conversion optimization) at scale, and understand the nuances of optimizing for user engagement, relevance, and long-term value under latency constraints.\n\nYou bring hands-on experience developing and deploying large-scale models, with an appetite for pushing state-of-the-art techniques and advancing model capability through increased scale and complexity. You are motivated by privacy-preserving machine learning and have experience building systems that operate effectively within privacy-first constraints.\n\nIn this role, you will lead the strategy and development of inference models that predict and optimize user interactions with ads, working across the full modeling stack-from data and model training pipelines to real-time serving and experimentation. You will partner closely with engineering and product teams to define and execute a forward-looking roadmap. You thrive in a fast-paced, Agile environment and are a hands-on ML leader who can drive execution while building strong, collaborative teams.
10 years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data sets\nYou can actively participate in investigations into multiple streams of ads quality data, and draw conclusions from data, recommend actions\nYou have experience in some of the following domains: Algorithms, Architecture, Artificial Intelligence, Database Systems, Data Mining, Distributed Systems, Machine Learning, Networking, Statistics, Game Theory, Auction Design, or other experience with rigorous Quantitative Analysis or Systems Software implementation\nPractical understanding of the mathematics behind modern machine learning, linear algebra and statistics\nYou have experience developing and leading teams who develop in Python or Java\nYou are familiar with databases, SQL, and scripting languages\nProven ability to take requirements from design through to implementation both independently and with larger teams\nYou thrive working closely with operational teams on deployment, monitoring, and management concerns\nYou actively manage performance of the team reporting to you and take responsibility to drive its outcome\nPhD or MS in AI/ML/Mathematics/CS or related field
10 years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data setsPhD in AI/ML/Mathematics/CS or related field