Senior Applied ML Scientist – Generative Video
Apple - Cupertino, United States of America
Posted Jan 9, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Verification
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- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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- Weekend work
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About this role
Senior Applied ML Scientist – Generative Video Cupertino, United States of America We are looking for a passionate Senior Applied ML Researcher to drive innovation in generative video modeling, with a strong focus on diffusion-based methods and related generative features. In this role, you will research, design, and deploy models at the intersection of machine learning research and real-world product impact. You will collaborate closely with research scientists, engineers, and product teams to find novel applications of generative AI capabilities to assist our creative user base. Your mission is to elevate the workflows of millions of creators by combining generative AI with Apple's human-centered design principles. Design and train state-of-the-art generative video models, primarily based on diffusion, consistency, rectified flow, or related generative frameworks Explore novel architectures for spatiotemporal modeling (e.g., 3D U-Nets, DiT-style Transformers, hybrid CNN-Transformer models) Conduct experiments on long-range temporal coherence, motion consistency, controllability, and multi-modal conditioning (text, audio, images) Minimum Qualifications: MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience 4+ years of experience in deep learning for generative models, particularly diffusion-based methods Hands-on experience in distributed training of large models using PyTorch (or equivalent frameworks) Solid understanding of video representations, spatiotemporal modeling, and neural network optimization. Experience designing & training multi-modal DiT-style Transformers, latent diffusion, or multi-stage video generation pipelines Experience design & training adapters Proven ability as a creative problem solver Preferred Qualifications: PhD with research focused on generative modeling, diffusion models, or video understanding Experience with text-to-video, image-to-video,
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