Founding Applied Scientist, Knowledge & Personalization AI

Amazon

San Francisco, Northern (CA, KY)

Hybrid

USD 143,000 - 193,000

Full time

14 days+
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Job summary

Amazon.com Services LLC in Seattle is seeking a researchers who will own end-to-end AI memory problems, from data collection to production. You will design, run and scale experiments, and ship effective models that drive real-world outcomes.

You will collaborate with scientists, engineers and PMs across the organization, mentoring juniors and shaping the team’s research direction in knowledge-reasoning and information retrieval.

Qualifications

  • 3+ years of building models for business applications.
  • PhD, or Master’s degree with 4+ years of CS, CE, ML or related field experience.
  • 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.
  • Experience in designing experiments and statistical analysis of results.
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals.

Responsibilities

  • Solve real-world problems by getting and analyzing large amounts of data, generating insights and opportunities, executing experiments, and developing statistical and ML models.
  • Collaborate with Scientists, Engineers, and Product Managers across the organization to influence stakeholders with clear communication.
  • Mentor junior members and help them grow.

Skills

Model building
Java
C++
Python
Algorithms and data structures
Data mining
Parallel computing
Numerical optimization
Publications or patents

Education

PhD or Master’s with CS/CE/ML focus

Job description

Amazon.com Services LLC in Seattle is seeking a researchers who will own end-to-end AI memory problems, from data collection to production. You will design, run and scale experiments, and ship effective models that drive real-world outcomes.

You will collaborate with scientists, engineers and PMs across the organization, mentoring juniors and shaping the team’s research direction in knowledge-reasoning and information retrieval.

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