mid Machine Learning Engineer ic Master's · Posted Jul 1, 2026

About this role

Apple is hiring a mid-level Machine Learning Engineer based in Beijing, China. The posting calls out experience with Python, PyTorch, Computer Vision, Deep Learning. Listed education preference: a master's degree or equivalent.

Role
Machine Learning Engineer
Function
machine learning
Level
mid
Track
Individual contributor
Location
Beijing, China
Education
Master's degree
Department
Machine Learning and AI
Posted
Jul 1, 2026
AI Summary
Develop and optimize state-of-the-art video generation models using diffusion and transformer techniques for on-device deployment across Apple products. Requires M.S./Ph.D. in Computer Science or related field with strong expertise in generative video modeling, temporal modeling, or frame interpolation, plus proficiency in PyTorch/JAX and large-scale training pipelines.

Job description

from Apple careers

If you are passionate about advancing video generation, building state-of-the-art models that synthesize high-quality and controllable video, and optimizing them for on-device deployment, 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 AI.
As part of Apple’s Video Engineering org, you will develop models and infrastructure for video generation and understanding across Apple products. You will work on cutting-edge generative techniques, from diffusion and transformer-based models to frame interpolation and temporal modeling, while ensuring models run efficiently on iPhone, iPad, and Vision Pro. You will collaborate with research scientists, framework engineers, and cross-functional teams to design, train, optimize, and deploy scalable video generation systems.
<h3>Minimum Qualifications</h3>M.S. or Ph.D. in Computer Science, Electrical Engineering, or related fields with focus on computer vision or machine learning.
Strong experience in one or more of: generative video modeling, video prediction, temporal modeling, or frame interpolation.
Proficiency in deep learning frameworks (PyTorch, JAX) and programming languages (Python, C++).
Experience with large-scale training pipelines and deploying models in real-world systems.
Strong written and verbal communication skills.
<h3>Preferred Qualifications</h3>Publications in top-tier conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR).
Experience with multi-modal video or text-video generation.
Familiarity with optimizing generative models for mobile/embedded devices.
Understanding of temporal consistency, controllable generation, and efficient infrastructure for large-scale video modeling.
Passion for building scalable, high-quality systems in cross-functional teams.

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