Computer Vision / Machine Learning Intern (Video Intelligence)

If you are passionate about advancing video understanding, video generation, and photography intelligence, and are driven to pursue excellence, embrace challenges, collaborate with others, and learn new things along the way, Apple is the right place for you. We are looking for engineers who combine deep technical expertise, creativity, and systems thinking to push the boundaries of video intelligence.

Description

The Video Intelligence Intern will join the China Vision Lab under the Video Engineering organization, contributing to the development of on-device computer vision and machine perception technologies across Apple’s ecosystem.

In this role, you will design and implement cutting-edge machine learning systems in areas such as video understanding, video generation, and photography intelligence. You will work on advanced algorithms and models that are optimized to run efficiently across a range of Apple products, including iPhone, iPad, and Vision Pro.

This position offers a unique opportunity to bridge research and product, delivering state-of-the-art experiences to millions of users. You will collaborate closely with cross-functional teams to drive innovation across the full technology stack and help bring new ideas from concept to production.

Minimum Qualifications

Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Electrical Engineering, or a related field
Strong foundation in computer vision and machine learning
Experience with deep learning frameworks such as PyTorch or TensorFlow
Solid programming skills in Python and/or C++
Familiarity with video processing, image understanding, or generative models

Preferred Qualifications

Publications in top-tier conferences (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH)
Solid understanding and industry experiences on computational photography, visual perception or reasoning algorithms, MLLM, diffusion models, etc
Familiarity with optimizing algorithms that run efficiently on mobile/embedded platforms
Strong problem-solving skills and ability to work in a fast-paced environment
Team oriented, result oriented, and self motivated