Sr. Applied Scientist, Prime Video - Generative AI

Amazon Amazon · Big Tech · Sunnyvale, CA · Machine Learning Science

This role focuses on researching and developing generative AI models for content localization, image/video understanding, and personalization within Prime Video. Key responsibilities include innovating on diffusion and flow-based methods, advancing visual grounding and 3D estimation, and designing multimodal GenAI workflows with agentic pipelines. The role aims to deliver production-ready generative AI systems at Amazon scale.

What you'd actually do

  1. Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia
  2. Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability.
  3. Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines.
  4. Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines.

Skills

Required

  • building machine learning models for business application
  • PhD or Master's degree and 6+ years of applied research experience
  • Java, C++, Python or related language
  • neural deep learning methods
  • machine learning

Nice to have

  • R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy
  • large scale distributed systems such as Hadoop, Spark

What the JD emphasized

  • end-to-end ownership
  • applying advanced machine learning techniques
  • Generative AI
  • multimedia understanding
  • content localization
  • content personalization
  • controllable synthesis
  • diffusion and flow-based methods
  • parameter efficient training
  • test-time adaptation
  • visual grounding
  • depth and 3D estimation
  • segmentation
  • matting
  • multimodal GenAI workflows
  • visual-language model tooling
  • structured prompt orchestration
  • agentic pipelines
  • production-ready systems
  • Amazon scale

Other signals

  • Generative AI
  • multimedia understanding
  • content localization
  • content personalization
  • controllable synthesis
  • diffusion models
  • flow-based methods
  • visual grounding
  • depth estimation
  • 3D estimation
  • segmentation
  • matting
  • multimodal GenAI workflows
  • visual-language model tooling
  • structured prompt orchestration
  • agentic pipelines