Develops and trains large-scale diffusion models for image/video generation, controllability modules like IPAdapters/ControlNets, and novel research techniques for production. Requires proven experience with image/video models at scale and deep learning frameworks.
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About the role
Responsibilities
Train foundation diffusion models for image and video generation.
Train controllability modules such as IPAdapters or ControlNets.
Develop novel research techniques and put them into production.
Conduct large-scale experiments on high-performance computing clusters, optimizing data pipelines for massive image datasets.
Requirements
Proven track record in working with image or video models at scale (publications or open-source contributions a plus).
Strong background in deep learning frameworks and distributed training paradigms.
Ability to iterate rapidly, and propose creative research directions.
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