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Senior Applied Scientist, Prime Video - Content Generation Team

Amazon.com

$150,400 - $260,000
Aug 25, 2025
Sunnyvale, CA, US
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Prime Video is looking to push the envelope of content localization and generation by developing state-of-the-art machine learning models and systems.

Requirements

  • 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
  • Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
  • Publications at top-tier peer-reviewed conferences or journals in one of those areas (computer vision, graphics, machine learning)

Responsibilities

  • Be the technical leader in machine learning; lead efforts within this team and across other teams.
  • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase customer engagement and monetization.
  • Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity.
  • Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with product managers and engineers to assist in productionizing your models.
  • Run experiments, gather data, and perform statistical analysis.
  • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
  • Research new and innovative machine learning approaches.

Other

  • Be the technical leader in machine learning; lead efforts within this team and across other teams.
  • Recruit scientists to the team and provide mentorship.
  • Share knowledge and research outcomes via internal and external conferences and journal publications
  • work safely and cooperatively with other employees, supervisors, and staff
  • adhere to standards of excellence despite stressful conditions