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Apple

# Machine Learning Research Engineer, App Store Search

Seattle, United States of America Data & Analytics 

Listed on Apple’s official careers site. Posted July 20, 2026. Check that it is still open and apply there.
[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200671370/machine-learning-research-engineer-app-store-search)

[OpenNash Jobs](https://jobs.opennash.com/) / [Apple](https://jobs.opennash.com/companies/apple/) / Machine Learning Research Engineer, App Store Search

## Job description

The Apple Services Engineering (ASE) team is one of the most exciting examples of Apple's long-held passion for combining art and technology. People here create the experiences loved by users across App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. The scale is massive â delivering content and entertainment in over 35 languages to more than 150 countries, while meeting Apple's high bar on quality and performance.

The team is responsible for building secure, robust, end-to-end solutions across server and client to solve challenging problems. Thanks to Apple's unique integration of hardware, software, and services, engineers here work with a single unified vision of deep commitment to strengthening Apple's core principles such as customer focus, privacy, and relentless innovation. Although services are a bigger part of Apple's business than ever before, these teams remain small, nimble, and cross-functional, offering an opportunity to work with passionate people, contribute ideas, and ship innovative software.

Here, you'll do more than just join a team â you'll be creating positive impact in people's lives.

## At a glance
- Posted by the employer: Jul 20, 2026
- First seen by OpenNash: Aug 20, 2026
- Last checked: Oct 18, 2026
- Listed for: 90 days
- Location: Seattle, United States of America[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200671370/machine-learning-research-engineer-app-store-search)

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Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

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