Job Details

Weekly Hours: 40

Role Number: 200631347-0836

Summary

Apple devices capture and edit trillions of photos every year, and maintaining Apple’s
high standards of visual quality at this scale requires innovation at every level of the
imaging pipeline. We’re forming a new team within the Camera and Photos Software
group to rethink how we assess and scale image quality—both objectively and
subjectively—across features and workflows.

Description

We’re looking for a highly motivated research engineer with a strong background in
machine learning and image quality assessment. In this role, you’ll design and develop
state-of-the-art ML-based algorithms to evaluate and enhance visual quality, partnering
closely with cross-functional teams to ensure Apple’s camera and photo experiences
consistently exceed expectations.

Minimum Qualifications

• 2+ years of industry or academic experience in image quality assessment.

• Strong background in ML techniques, with experience in one or more of the following: Transformers, LLMs, VLMs.

• Proficiency in Python and deep learning frameworks such as PyTorch.

• Solid foundation in digital signal and image processing.

• Master's degree in Artificial Intelligence, Machine Learning, Computer Science, Electrical/Computer Engineering, or a related field.

Preferred Qualifications

• Experience working AI-based solutions for large-scale, real-world image or video data and performance-sensitive applications.

• Familiarity with human perception models and subjective testing methodologies.

• Demonstrated ability to translate research into production-level code and tools.

• Familiarity with iOS and/or macOS development environments, tools, and APIs.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .