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Machine Learning Engineer, Computer Vision
Apple Inc. · Posted 7 days ago
Build computer vision and VLM models that ship on millions of Apple devices and power features like Visual Intelligence and Clean Up in Photos.
Summary: We are looking for a Machine Learning Engineer with strong foundations in computer vision and machine learning, and a practical mindset: you care about making models work on real data, in real products. Our team builds foundational perception technologies. These models are built once and reused by many experiences, across iPhone, iPad, Mac, HomeView and more. They already power Apple Intelligence features such as Visual Intelligence and Clean Up in Photos. Our work spans a wide range of models, from lightweight, task-specific vision models to general-purpose vision-language models. In this role, you will build computer vision models and VLMs that help Apple devices recognize and understand the objects around the user. You will turn recent research into models that ship on millions of devices.
Description: Design, train and improve computer vision and VLM models for object understanding and recognition. Make models robust to real-world conditions and across devices and fix failure modes on real data Define evaluations that reflect product quality, and use them to drive model decisions. Design models for on-device constraints (memory, latency, power).
Minimum Qualifications: Ph.D. or Master's in Computer Science, Machine Learning, Computer Vision or a related field, or equivalent industry experience. Strong foundations in computer vision and deep learning. Track record of making models work in practice: end-to-end projects covering data, training and evaluation on real-world visual data. Proficiency in Python and PyTorch or an equivalent deep learning framework. Proficiency in using generative coding tools Rigorous experimentation: clear baselines, ablations and meaningful evaluation sets.
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There are 543 open roles at Apple Inc. right now. This role is one of 567 Machine Learning Engineer openings and centers on Python, Pytorch, Computer Vision, and Deep Learning.
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