Machine Learning Engineer
San Francisco, CAML EngineeringOnsite
Summary
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.
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.
Skills
Diffusion ModelsIPAdaptersControlNetsDeep LearningPyTorchTensorFlowDistributed TrainingImage GenerationVideo GenerationHigh-Performance Computing