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# Machine Learning Video Process Engineer

- **Company:** Apple Inc.
- **Location:** Cupertino, CA, United States
- **Salary:** $126,800.0 - $220,900.0
- **Contract:** Permanent contract
- **Skills:** Computer Programming, Computer Engineering, Noise Reduction, Python (Programming Language), Machine Learning, Video Editing, Pytorch, Deep Learning, Information Technology, Software Library
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0d6e40aab9a50dfb

## About the Role

Do you have experience in Machine learning libraries?, Do you have a Master's degree?, PhD or Masters degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields

Knowledge of low-level vision algorithms such as spatial and temporal image/video scaling, noise reduction, etc.

Background in digital signal and image processing

Publication record in top-tier conferences (e.g., CVPR, ICCV, SIGGRAPH, ECCV, NeurIPS, ICML, ICLR)

Excellent independent problem-solving skills

Excellent written and oral communication skills

Minimum Qualifications

Minimum requirement of a bachelors degree

Masters degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields

Knowledge of the principles, algorithms, and techniques used in machine learning and video processing with first-hand experiences.

Programming skills and hands-on experience with Python and deep learning frameworks such as PyTorch

## Description

We are looking for a Machine Learning Video Processing Engineer who will join us to build Apple's next-generation video processing algorithms. In this role, you will identify and develop machine leaning solutions and work closely within a dynamic team to optimize and productize those features. Your responsibilities include, but not limited to:","responsibilities":"Develop and maintain data collection, processing, and curation pipelines to support model training, validation, and testing.

Design and implement deep learning algorithms for low-level vision tasks.

Optimize models and algorithms for performance, including latency, memory, and computational efficiency.


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