Machine Learning Engineer, Computer Vision

Apple • Cupertino, CA

4h

About The Position

Apple is seeking a Machine Learning Engineer with strong foundations in computer vision and machine learning and a practical focus on making models work on real data in real products. The team builds foundational perception technologies that are reused across experiences on iPhone, iPad, Mac, HomeView, and other platforms. These technologies power Apple Intelligence features such as Visual Intelligence and Clean Up in Photos.

The work spans lightweight, task-specific vision models and general-purpose vision-language models. In this role, you will build computer vision models and VLMs that help Apple devices recognize and understand nearby objects, translating recent research into models that ship on millions of devices. You will design, train, and improve models for object understanding and recognition; make them robust across real-world conditions and devices; evaluate product quality; and design models for on-device memory, latency, and power constraints.

Requirements

• Ph.D. or Master's degree 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, including 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, including clear baselines, ablations, and meaningful evaluation sets.

Nice To Haves

• Publications in leading computer vision or machine learning venues such as CVPR, ICCV, ECCV, NeurIPS, or ICLR, ideally with released code or work transferred to a product.
• Experience in representation learning, such as self-supervised learning, metric learning, retrieval, or recognition.
• Experience applying machine learning in an industry or product setting.
• Experience with knowledge distillation or model compression.
• Familiarity with vision-language models.

Responsibilities

• Design, train, and improve computer vision and vision-language models for object understanding and recognition.
• Make models robust to real-world conditions and across devices, and address failure modes on real data.
• Define evaluations that reflect product quality and use them to guide model decisions.
• Design models for on-device memory, latency, and power constraints.
• Turn recent research into models deployed on millions of devices.

What This Job Offers

• Job Type: Full-time