Senior Machine Learning Manager, Apple Services Engineering AI​/ML

Senior Machine Learning Manager, Apple Services Engineering AI/ML

Cupertino, California, United States Machine Learning and AI

The Apple Services Engineering (ASE) AI/ML organization is looking for an experienced Manager to help build next‑generation media discovery experiences for Apple's groundbreaking devices and platforms, leveraging Artificial Intelligence & Machine Learning der how Apple's Media Products show relevant and rich Discovery experiences covering search, browse and recommendations for Apple's media offerings – including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books?

Come join us! Research, design and develop AI/ML driven Discovery features for billions of Apple users worldwide! Propose, prototype and evaluate algorithm improvements that power these rich experiences. Evangelize and build reusable AI capabilities to enhance the foundation of how these user‑facing features are built in the larger organization. The ASE organization is one of the most exciting examples of Apple’s long‑held passion for combining art with technology.

We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And we do it on a massive scale, meeting Apple’s high expectations with high performance, to deliver a huge variety of entertainment in over 40 languages to more than 170 countries. Our scientists and engineers build secure, end‑to‑end solutions powered by Artificial Intelligence & Machine Learning.

Thanks to Apple’s unique integration of hardware, software, and services, designers, scientists and engineers in ASE partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple’s privacy policy, one of Apple’s core values. Although services are a bigger part of Apple’s business than ever before, these teams remain small, flexible, and multi‑functional, offering greater exposure to the array of opportunities here.

This is a frontline management role, managing a team of Applied Researchers. You’ll shape both the technical and product direction, driving the integration of cutting‑edge advancements in Machine Learning, Natural Language Processing, and Generative AI to transform how users discover Apple Media content across devices worldwide. You’ll be joining a team with deep expertise in Information Retrieval, Machine Learning, Language Modeling, Generative AI, Data Mining, and Distributed Computing technologies such as Hadoop, Scala, and Spark.

You will use data‑driven analysis to generate ideas, evaluate and prioritize features, and conduct A/B tests to ensure we objectively measure improvements. You will ensure successful delivery of features, code, data, and models into production. Collaboration will be key, you will work with researchers, engineers, and operations teams to ensure that features and models are functioning at or above expectations globally, in languages from Arabic to Vietnamese and everything in between!

• Lead and mentor ML researchers and engineers.
• Foster a culture of technical excellence, innovation, and collaboration.
• Set team goals, manage project timelines, and ensure high‑quality deliverables.
• Stay ahead of advancements in LLMs, transformer architectures, and multimodal models.
• Evaluate and adopt cutting‑edge models, toolkits, and frameworks.
• Oversee end‑to‑end development of NLP and GenAI models: from data collection and preprocessing to training, evaluation, and deployment.
• Guide implementation of applications such as summarization, question answering, chatbots, information retrieval, semantic search, and text generation.
• Ensure responsible AI practices including model fairness, bias mitigation, and explainability.
• Work closely with product managers, engineers, data science teams, and business stakeholders to align technical solutions with user needs.
• Translate research breakthroughs into real‑world applications that drive user and business value.
• Encourage publishing, patenting, and collaboration with other AI/ML teams.
• Drive experimentation with foundation models, retrieval‑augmented generation (RAG), fine‑tuning, prompt engineering, and…