Sr. Design Technologist, Prime Video - AI Content Generation
Amazon - Culver City, California, USA
Posted Apr 9, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
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- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
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About this role
Sr. Design Technologist, Prime Video - AI Content Generation Culver City, California, USA Prime Video is one of the world's leading streaming services, home to award-winning Amazon Originals, live sports, and a catalog spanning thousands of titles across every genre. Our creative and technology teams work together to deliver experiences that connect hundreds of millions of customers to the stories they love. We are looking for a Sr. Design Technologist who sits at the intersection of generative AI research and visual storytelling. Someone who can go deep on the technical architecture of diffusion and autoregressive models, then turn around and speak fluently with a creative director about narrative, tone, and image craft. This role is the connective tissue between our ML science teams and our creative production teams - and the person who fills it will shape how both sides work together to define what AI-generated content means for a world-class streaming service. Key job responsibilities - Serve as the primary liaison between Science/ML teams and Creative/Production teams - translating research capabilities into production workflows, and translating production needs into requirements scientists can build against - Develop deep working knowledge of the generative models being built and evaluated internally, assessing them through both a technical and artistic lens - Work with production teams to understand their creative workflow needs, then partner with science teams to scope and prioritize what gets built - Build proof-of-concept workflows and tooling that demonstrate how new model capabilities apply to real content production problems -
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