Senior Machine Learning Engineering Manager – Ads Predictions

Senior Machine Learning Engineering Manager – Ads Predictions

Cupertino, California, United States Software and Services

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 sponsor ships 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.

You 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. In 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.

• Lead and grow a high‑performing, team of ML engineers and applied scientists focused on Ads Response Predictions across different surfaces
• Partner cross-functionally with Engineering, Product and Sales teams to deliver end-to-end solutions from ideation to production
• Collaborate closely with platform and infrastructure teams to optimize training, inference, and resource utilization for large‑scale ML workloads
• Drive development and deployment of state‑of‑the‑art machine learning models (including large‑scale neural networks and LLM‑based systems) for ads quality and marketplace optimization
• Own the full lifecycle of ML systems—data, modeling, offline evaluation, online experimentation, and productionization at scale
• Lead A/B experimentation strategy and decision‑making, translating complex data insights into clear product and business recommendations
• Ensure robust system design across modeling, feature pipelines, and online serving, with a focus on scalability, latency, and reliability
• Champion privacy‑preserving machine learning approaches in model development, data usage, and system design
• Set a high bar for technical excellence, code quality, and operational rigor, including monitoring, debugging, and continuous improvement of production systems
• Mentor and develop team members, actively managing performance and fostering a culture of ownership, innovation, and execution
• Communicate effectively with senior leadership, distilling complex technical concepts into clear, actionable insights and strategy

• 10+ years applying and leading teams that apply advanced statistical/ML methods and work with large, complex data sets
• You can actively participate in investigations into multiple streams of ads quality data, and draw conclusions from data, recommend actions
• You 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…