Applied Scientist Ii, Conversational Ad Experiences

Amazon Amazon · Big Tech · Seattle, WA · Machine Learning Science

The role focuses on applying generative AI and LLMs to create conversational ad experiences for Amazon. Responsibilities include defining science roadmaps, building and deploying models, running experiments, and collaborating with engineers and product managers. The goal is to enhance customer experience and advertiser reach through innovative AI solutions in the advertising domain.

What you'd actually do

  1. Serve as a tech lead for defining the science roadmap for multiple projects in the conversational ad experiences space powered by LLMs.
  2. Build POCs, optimize and deploy models into production, run experiments, perform deep dives on experiment data to gather actionable learnings and communicate them to senior leadership
  3. Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.
  4. Work closely with product managers to contribute to our mission, and proactively identify opportunities where science can help improve customer experience
  5. Research new machine learning approaches to drive continued scientific innovation

Skills

Required

  • building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • generative AI
  • LLMs
  • conversational contexts
  • multi-turn interfaces
  • generative AI
  • large language models (LLMs)
  • information retrieval
  • ads recommendation systems
  • generative AI
  • online experimentation

Other signals

  • generative AI
  • LLMs
  • conversational interfaces
  • recommendation systems
  • online experimentation