Machine Learning Research Engineer - Image Quality
Apple
Software Engineering, Data Science, Quality Assurance
Cupertino, CA, USA
USD 147,400-272,100 / year + Equity
Posted on Nov 13, 2025
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.
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.
- Research and develop advanced AI / ML models for image and video quality assessment.
- Explore and apply emerging technologies including Vision-Language Models (VLMs) and Large Language Models (LLMs) to visual quality tasks.
- Collaborate with experts across camera, imaging, and ML teams to define quality metrics that align with both subjective experience and objective benchmarks.
- Prototype, validate, and iterate on models using real-world image data from Apple’s imaging pipeline.
- 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.
- 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.
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