Sr. Machine Learning Manager, AI, Search & Knowledge Platforms

Do you want to make Apple products more intelligent for our users? The Search & Recommendation Platforms team is building groundbreaking core infrastructure technology for an AI powered, large scale, highly performant agentic search serving stack. This platform powers search and recommendation experiences across Siri, Safari, Spotlight, App Store, Apple Music, and other Apple products.

We are looking for a seasoned Engineering Manager who will build and lead a team of backend infrastructure and ML engineers, own the technical roadmap for large scale indexing and serving systems, and drive execution against aggressive scale, reliability, latency, and cost targets.

We design and build the core infrastructure that indexes and serves billions of documents to find and return the best content to users at query time, with high throughput and low latency. This infrastructure underpins LLM powered and agentic search, spanning indexing, semantic and multimodal retrieval, query understanding, model inference, and agentic orchestration. This roles focus is indexing and serving specifically. As the manager of this team, you will set technical direction, grow and develop your team, and partner across quality, infra, and product teams to prioritize what gets built. You will have the opportunity to lead work spanning hundreds of billions of documents, petabytes of data, and real time evaluation pipelines.

Deep expertise in web scale indexing systems, including distributed document processing, storage, and retrieval Strong coding skills and background in algorithms and data structures 10+ years of experience leading and driving complex, large scale search infrastructure projects Experience managing managers and engineering teams, including hiring, growth, and performance management Track record scaling engineering teams across multiple sites/geographies Strong technical judgment and ability to drive architecture, execution, and cross functional alignment across complex programs spanning multiple teams BS, MS, or Ph.D. in Computer Science or related field Experience designing evaluation infrastructure for large scale indexing and retrieval systems Experience with RAG and agentic search scenarios Track record of driving developer velocity and quality improvements across large engineering organizations Familiarity with LLM model inference, and search quality metrics