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# Machine Learning Engineer

- **Company:** Apple Inc.
- **Location:** Cupertino, CA, United States
- **Salary:** $150,400.0 - $225,300.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, Computer Programming, Python (Programming Language), Machine Learning, Pytorch, Deep Learning, Generative AI, Information Technology
- **Published:** September 17, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ba807b8f961ce8d9

## About the Role

Advanced Generative AI Applications: practical experience in the design, training, and fine-tuning of complex generative AI architectures, encompassing diffusion models, autoregressive models, GANs, and VLMs.

Computer Vision Foundation: Robust theoretical and practical foundation in core computer vision principles, particularly applied to image and video analysis and processing.

Analytical & Communication Skills: Exceptional analytical problem-solving capabilities and technical communication skills, essential for cross-functional collaboration and presenting complex research.

Proven Research: Publication record in highly selective, peer-reviewed conferences (e.g., CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, ICML, ICLR)

Minimum Qualifications

Generative AI Expertise: Strong understanding and practical experience with advanced generative AI architectures, including (but not limited to) diffusion models, Generative Adversarial Networks (GANs), and autoregressive models.

Technical Proficiency: Strong programming skills in Python and deep learning frameworks (e.g., PyTorch).

An MS or PhD in Computer Science, Engineering, or a related technical discipline.

## Description

As a Machine Learning Engineer, you will be instrumental in driving the innovation of Apple's next-generation iPhone and iPad camera algorithms. You will identify, research, and develop cutting-edge generative AI-based machine learning models to address complex challenges in camera applications. You will collaborate cross-functionally with GPU optimization and framework teams to seamlessly integrate and deploy these advanced features into production, directly shaping the future of mobile imaging.


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