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Senior Applied ML Scientist – Generative Video

Job in Cupertino, Santa Clara County, California, 95014, USA
Listing for: Apple Inc.
Full Time position
Listed on 2026-01-12
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, AI Engineer, Artificial Intelligence
Salary/Wage Range or Industry Benchmark: 181100 - 318400 USD Yearly USD 181100.00 318400.00 YEAR
Job Description & How to Apply Below

Senior Applied ML Scientist – Generative Video

Cupertino, California, United States Software and Services

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.

Description
  • 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, cont rollability, 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.
  • 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, or video-to-video generation.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including:
Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note:

Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

Apple accepts applications to this posting on an ongoing basis.

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Position Requirements
10+ Years work experience
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