Applied Scientist - Personalization & Recommendations

Amazon Science

Seattle (WA)

On-site

USD 143,000 - 193,000

Full time

7 days ago
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Benefits offered by this job

Health insurance
401(k) matching
Paid time off

Job summary

Amazon Science in Seattle is seeking researchers to build state-of-the-art recommendation and personalization models at scale, impacting how millions discover products and experiences. Join AWS AI initiatives to develop scalable systems and publish your findings in top venues.

You will collaborate with cross-functional teams, leverage vast data, and work on foundational models and LLMs in recommendation pipelines. This role emphasizes innovation, mentorship, and a strong publication record.

Qualifications

  • 3+ years of building models for business application experience.
  • PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience.
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals.
  • Experience programming in Java, C++, Python or related language.
  • Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Responsibilities

  • Develop and evaluate state-of-the-art recommendation and personalization models.
  • Collaborate with researchers and engineers to deploy models at scale.
  • Publish findings at peer-reviewed conferences and journals.

Skills

Java
C++
Python

Education

PhD, or Master’s degree with 4+ years CS/CE/ML

Tools

Unix/Linux

Job description

Amazon Science in Seattle is seeking researchers to build state-of-the-art recommendation and personalization models at scale, impacting how millions discover products and experiences. Join AWS AI initiatives to develop scalable systems and publish your findings in top venues.

You will collaborate with cross-functional teams, leverage vast data, and work on foundational models and LLMs in recommendation pipelines. This role emphasizes innovation, mentorship, and a strong publication record.

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