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Apple

# Machine Learning Engineer, Evaluation and Quality, Creativity Apps

San Diego Metro Area, United States of America Data & Analytics 

Listed on Apple’s official careers site. Posted October 27, 2026. Check that it is still open and apply there.
[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200691707/machine-learning-engineer-evaluation-and-quality-creativity-apps)

[OpenNash Jobs](https://jobs.opennash.com/) / [Apple](https://jobs.opennash.com/companies/apple/) / Machine Learning Engineer, Evaluation and Quality, Creativity Apps

## Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Creativity Apps team is looking for a Machine Learning Engineer focused on the quality and evaluation of ML models and AI features in our creativity applications. You will define how we measure whether the product and AI features are good enough to ship: designing the evaluation strategy and metrics, building the datasets and infrastructure behind them, and driving end-to-end quality from model development through to the feature in customers' hands.

You will have the unique and rewarding opportunity to help shape upcoming products that will delight and inspire millions of creators every day.

## At a glance
- Posted by the employer: Oct 27, 2026
- First seen by OpenNash: Nov 1, 2026
- Last checked: Nov 1, 2026
- Listed for: 5 days
- Location: San Diego Metro Area, United States of America[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200691707/machine-learning-engineer-evaluation-and-quality-creativity-apps)

## Hiring at Apple
- Open jobs: 6,319
- New in the last 7 days: After two weekly collections
- Tracked since: Jul 10, 2026

[All Apple jobs](https://jobs.opennash.com/companies/apple/) · [Weekly hiring report](/reports/hiring/)

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

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