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Machine Learning Engineering Manager - On device modeling
Apple
H1B ✓On-sitemanagerPosted April 19, 2026
About the Role
Lead a team of applied ML engineers to develop LLMs and NLP models for Siri's personal domain understanding. Own the engineering systems and models responsible for query understanding with a focus on on-device efficiency and privacy.
Requirements
Requires 6+ years of industry experience in ML, NLP, and AI, along with 2+ years of technical leadership or management experience. Candidates must possess strong software engineering fundamentals and deep knowledge of ML architectures and inference optimization.
Full Job Description
The AI represents a unique opportunity to elevate Apple’s products and revolutionize the way hundreds of millions of people access information on their devices. As an Applied ML team, we're pushing the boundaries of Apple Intelligence and innovative search technologies, all while running a low latency production service and keeping user privacy at the forefront.
We are looking for a Machine Learning Engineering Manager with a passion for using latest AI advances to build on device models and systems that will power intelligent search applications. Our team researches and implements novel query understanding models and machine learning algorithms, focusing on low footprint on-device solutions, that power innovative search experiences across Apple products.
In this role you will have the opportunity to lead a team of applied ML engineers to develop LLMs and other NLP models for improving Siri's ability to understand personal domain questions and power intelligent search of on-device content. Our team owns models and engineering systems responsible for query understanding of users' questions about their personal content, with a focus on on-device models and systems that put user privacy and efficiency at the forefront. Our solutions integrate with other Siri and Search capabilities to enable powerful user experiences.
6+ years industry experience in Machine Learning, NLP, AI and applying these techniques for production applications 2+ years industry experience with technical leadership or management roles Deep understanding of ML fundamentals including neural network architectures, transformers, attention mechanisms, and inference optimization Strong software engineering fundamentals with expertise in systems design, API architecture, and distributed systems Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.) Strong communication skills
Prior experience in building on-device AI models and deploying them in production Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience
Description
In this role you will have the opportunity to lead a team of applied ML engineers to develop LLMs and other NLP models for improving Siri's ability to understand personal domain questions and power intelligent search of on-device content. Our team owns models and engineering systems responsible for query understanding of users' questions about their personal content, with a focus on on-device models and systems that put user privacy and efficiency at the forefront. Our solutions integrate with other Siri and Search capabilities to enable powerful user experiences.
Minimum Qualifications
6+ years industry experience in Machine Learning, NLP, AI and applying these techniques for production applications 2+ years industry experience with technical leadership or management roles Deep understanding of ML fundamentals including neural network architectures, transformers, attention mechanisms, and inference optimization Strong software engineering fundamentals with expertise in systems design, API architecture, and distributed systems Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.) Strong communication skills
Preferred Qualifications
Prior experience in building on-device AI models and deploying them in production Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience
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Compensation
AI Est. Total Comp
$450,000