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Apple

# Machine Learning Systems Engineer – Video Computer Vision

Sunnyvale, United States of America Data & Analytics 

Listed on Apple’s official careers site. Posted October 28, 2026. Check that it is still open and apply there.
[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200692165/machine-learning-systems-engineer-video-computer-vision)

[OpenNash Jobs](https://jobs.opennash.com/) / [Apple](https://jobs.opennash.com/companies/apple/) / Machine Learning Systems Engineer – Video Computer Vision

## Job description

The incredible potential of multimodal foundation models and large language models has unlocked machine learning applications that were previously thought infeasible. The Video Computer Vision (VCV) group is looking for a highly motivated and skilled Machine Learning Systems Engineer to help us ship cutting-edge computer vision technology on Apple devices. The VCV organization has pioneered groundbreaking features like FaceID/FaceKit, Gaze/Hand Gesture Control, Body Tracking, and 2D/3D Scene Understanding fundamentally changing how millions of users interact with technology.

We seamlessly balance research and product requirements to deliver pioneering, Apple-quality experiences. By innovating across the full stack and partnering closely with hardware, software, and AI teams, we shape future products and bring our architectural vision to life.

## At a glance
- Posted by the employer: Oct 28, 2026
- First seen by OpenNash: Nov 1, 2026
- Last checked: Nov 1, 2026
- Listed for: 4 days
- Location: Sunnyvale, United States of America[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200692165/machine-learning-systems-engineer-video-computer-vision)

## 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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