Research Scientist, Generative Media

Snapshot

At Google Deep Mind, we've built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a highly motivated and experienced Research Scientist with strong engineering skills to join our team and contribute to groundbreaking fundamental research and deployment in Generative Media for images, videos and beyond.

Our team aims to build and improve state of the art generative models for images, videos and other modalities. We are interested in candidates with significant hands‑on experience in generative modeling techniques and who are familiar with the computer vision domain in general. You will need to be able to understand and work on the promising research directions, and implement them refore, both a strong technical background and hands‑on experience with large‑scale machine learning is required.

You will collaborate closely with other leading researchers, contributing to the development of cutting edge generative models and translating research into products across Google and externally.

We’re looking for a versatile Research Scientist, at ease both with figuring out how to approach new research questions, and the technical implementation of research ideas.

• Come up with ideas to solve new problems in Generative Media and improve performance and capabilities of existing models, e.g., developing, improving or evaluating the capabilities of models, or measuring outcomes.
• Develop technical solutions to test these ideas and assess performance.
• Report and present research findings and developments including results clearly and efficiently.
• Contribute to team collaborations to meet ambitious research goals.
• Engage with application and product needs, to inform research decisions.

In order to set you up for success as a Research Scientist at Google Deep Mind, we are looking for the following skills and experience:

• Ph.D. in computer vision, machine learning or closely related field.
• A proven track record of publications.
• Hands‑on experience with Python and neural network training
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• Ability to communicate technical ideas effectively, e.g. through discussions, whiteboard sessions, written documentation.

In addition, any of the following would be an advantage:

• Experience with controllable image and/or video generation
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• Good understanding of diffusion models
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• General experience in the computer vision domain.
• Hands‑on experience with large scale training of models
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• Experience translating research innovations into product applications.
• Understanding of safety and ethical concerns associated with generative models.