Computer Vision / Machine Learning Engineer (video Generation)

Apple Apple · Big Tech · Beijing, Beijing, China · Machine Learning and AI

This role focuses on developing and optimizing generative video models for on-device deployment across Apple products. It involves designing, training, and deploying state-of-the-art video generation systems, with a strong emphasis on efficiency and quality for consumer devices.

What you'd actually do

  1. Design and develop generative video models for high-fidelity, controllable synthesis.
  2. Build infrastructure for large-scale training, evaluation, and benchmarking of video models.
  3. Investigate model consolidation and shared representation learning across video understanding and generation tasks.
  4. Optimize algorithms for runtime, power, memory, and temporal quality on-device.
  5. Collaborate with product and research teams to integrate video generation technologies into Apple’s camera and video pipelines.

Skills

Required

  • 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.

Nice to have

  • 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.

What the JD emphasized

  • on-device deployment
  • optimize algorithms for runtime, power, memory, and temporal quality on-device
  • large-scale training
  • generative video modeling

Other signals

  • video generation
  • on-device deployment
  • generative techniques
  • large-scale training
  • optimize algorithms