Senior Applied Scientist, ML & Personalization

Prime Video & Amazon MGM Studios

Seattle (WA)

On-site

USD 143,000 - 193,000

Full time

19 hours ago
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Job summary

Amazon.com Services LLC in Seattle seeks a Prime Video technologist to own the product, user experience, design, and technology for state-of-the-art video experiences. You will tackle fast-paced, challenging projects and collaborate with engineers, researchers, and product managers.

You will contribute to foundation models, multimodal learning, and time-series analyses, publish your findings at conferences, and shape personalized recommendations across Prime Video on multiple devices.

Qualifications

  • PhD or Master’s degree in CS/CE/ML with 4+ years of relevant experience.
  • Proficient in Java, C++, Python and related languages.
  • Strong background in algorithms, data structures and software development practices.

Responsibilities

  • Develop foundation models for content understanding using state-of-the-art deep learning and multimodal techniques.
  • Build models to understand customer behavior and viewing trajectories.
  • Collaborate with engineers and product managers to design and ship end-to-end solutions.
  • Design and run offline and online experiments (A/B) with data-driven analyses.
  • Communicate complex technical concepts to teammates and stakeholders.
  • Stay current with advances in foundation models, multimodal learning, and time-series analysis.
  • Publish research findings in top conferences and journals.

Skills

Java
C++
Python
Unix/Linux

Education

PhD or Master’s in CS/CE/ML

Tools

Unix/Linux

Job description

Amazon.com Services LLC in Seattle seeks a Prime Video technologist to own the product, user experience, design, and technology for state-of-the-art video experiences. You will tackle fast-paced, challenging projects and collaborate with engineers, researchers, and product managers.

You will contribute to foundation models, multimodal learning, and time-series analyses, publish your findings at conferences, and shape personalized recommendations across Prime Video on multiple devices.

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