Applied Scientist, GenAI for Sponsored Ads & Brands

Amazon Inc.

New York (NY)

On-site

USD 172,000 - 223,000

Full time

14 days+

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Job summary

Amazon is seeking an Applied Scientist to innovate at the intersection of customer experience, deep learning, and GenAI within the SPB team. You will develop scalable GenAI models, collaborate with engineers to deploy end-to-end solutions, and advance real-time inference at Amazon Ads scale.

The role emphasizes building impactful GenAI capabilities, rigorous experimentation, and advancing state-of-the-art techniques to enhance advertising experiences across platforms.

Qualifications

  • 3+ years building models for business applications.
  • PhD or MS with 4+ years in CS/CE/ML or related field.
  • Experience programming in Java, C++, or Python.
  • Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, HPC.

Responsibilities

  • Leverage Generative AI and LLMs to mine behavioral data and derive shopper insights.
  • Design and develop scalable ML and GenAI models focused on shopper intent and preference.
  • Partner with engineering to deploy GenAI solutions into production and real-time systems.
  • Drive scalability and automation of large-scale model training and real-time inference.
  • Design and run rigorous A/B experiments to quantify business impact of GenAI insights.
  • Conduct applied research in novel generative AI techniques to optimize shopper experience.

Skills

Java/C++/Python
ML/GenAI
Distributed systems

Education

PhD or MS in CS/CE/ML

Tools

Unix/Linux
Software development

Job description

Amazon is seeking an Applied Scientist to innovate at the intersection of customer experience, deep learning, and GenAI within the SPB team. You will develop scalable GenAI models, collaborate with engineers to deploy end-to-end solutions, and advance real-time inference at Amazon Ads scale.

The role emphasizes building impactful GenAI capabilities, rigorous experimentation, and advancing state-of-the-art techniques to enhance advertising experiences across platforms.

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