Lead Generative AI Scientist, Video

Amazon

Culver City (CA)

On-site

USD 167,000 - 226,000

Full time

33 hours ago
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Benefits offered by this job

Health insurance
RSUs (restricted stock units)
Paid time off
Parental leave

Job summary

Amazon is seeking a Sr. Applied Scientist (Lead) for Prime Video Generative AI to drive state-of-the-art model development and production-ready systems.

You will lead research, experiments, and end-to-end delivery across vision, multimodal understanding, and GenAI, building scalable pipelines and large-scale capabilities. You will mentor teams, craft solutions for video production workflows, and push the boundaries of diffusion, flow-based methods, and video generation techniques to empower

Qualifications

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

Responsibilities

  • Lead end-to-end product journey, research and experimentation for this domain
  • Apply advanced ML techniques in Computer Vision, Multimedia Understanding and Generative AI
  • Design and implement production-ready GenAI systems at Amazon scale
  • Advance diffusion and flow-based methods to improve efficiency and controllability

Skills

ML model development
Generative AI
Programming: Java/C++/Python
Deep learning

Education

PhD or Master’s with 6+ years

Tools

R
scikit-learn
Spark MLLib
MxNet
TensorFlow
NumPy
SciPy

Job description

Amazon is seeking a Sr. Applied Scientist (Lead) for Prime Video Generative AI to drive state-of-the-art model development and production-ready systems.

You will lead research, experiments, and end-to-end delivery across vision, multimodal understanding, and GenAI, building scalable pipelines and large-scale capabilities. You will mentor teams, craft solutions for video production workflows, and push the boundaries of diffusion, flow-based methods, and video generation techniques to empower

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