Sr. Design Technologist, Prime Video - AI Content Generation

Amazon Amazon · Big Tech · Culver City, CA · Design

This role bridges generative AI research and visual storytelling for Prime Video, focusing on translating ML capabilities into production workflows and understanding creative needs. The Sr. Design Technologist will assess generative models, build proof-of-concept tools, and identify gaps between model output and production requirements.

What you'd actually do

  1. 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
  2. Develop deep working knowledge of the generative models being built and evaluated internally, assessing them through both a technical and artistic lens
  3. Work with production teams to understand their creative workflow needs, then partner with science teams to scope and prioritize what gets built
  4. Build proof-of-concept workflows and tooling that demonstrate how new model capabilities apply to real content production problems
  5. Identify and clearly articulate the gaps between what models currently produce and what production actually requires — to both sides of the table

Skills

Required

  • front-end technologist, engineer, or UX prototyper experience
  • coding samples in front end programming languages
  • Experience developing visually polished, engaging, and highly fluid UX prototypes
  • Experience collaborating with UX, Product, and technical partners

Nice to have

  • Knowledge of databases and AWS database services: ElasticSearch, Redshift, DynamoDB
  • Experience with machine learning (ML) tools and methods

What the JD emphasized

  • Experience with machine learning (ML) tools and methods

Other signals

  • translating research capabilities into production workflows
  • translating production needs into requirements scientists can build against
  • assess models through both a technical and artistic lens
  • build proof-of-concept workflows and tooling
  • identify and clearly articulate the gaps between what models currently produce and what production actually requires