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Machine Learning Systems Engineer, Siri Runtime Systems and Interaction

Apple · Cupertino, United States of America

Spotted 113d ago

Job details

Posted
Mar 3, 2026
Last confirmed open
Oct 21, 2026

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Job description

About this role

The Siri Team at Apple is actively looking for a highly motivated Systems Software Engineer to contribute to and build Apple's future technologies that power delightful Siri experiences supercharged with Apple Intelligence.

The successful candidate will be a skilled software engineer with strong ML fundamentals who enjoys problem-solving and is comfortable with designing, building, and optimizing system software that integrates machine learning capabilities.

Our team builds high-quality software that powers delightful Siri-based experiences in the Apple ecosystem. We value passion for excellence and a deep commitment to building high-quality software. If you want to impact millions of customers around the world by working on the most advanced technology solutions, we want to talk to you.

As a Machine Learning Systems Engineer in the Siri Group at Apple, you will work at the intersection of software engineering and machine learning, partnering with cross-functional teams to solve high-impact problems on Apple products.

Strong programming skills in Swift / C++ / Objective-C Solid understanding of machine learning concepts, model inference, and ML system design principles Experience developing and optimizing algorithms that run efficiently on resource-constrained platforms Passionate about delivering high-quality products, comfortable with ambiguity, intellectually curious and driven to find creative solutions Ability to thrive in collaborative environments with multiple cross-functional teams and communicate clearly with both engineering and ML teams BS (or higher) in Computer Science, Machine Learning, or related disciplines

Demonstrated experience building production-quality software Experience building ML infrastructure, evaluation pipelines, or training systems Familiarity with ML frameworks (Core ML, PyTorch, TensorFlow) and model optimization techniques

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