Drimva

Amazon

Applied Scientist, Advertising Trust

$143K–$223K

New York, NY +1 · Full-time · Posted Oct 15, 2026

Location
New York, NY
San Diego, CA
Experience
3+ years building models for business applications; PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.
Education
PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.

About the job

Build and deploy AI agents and machine-learning models that understand advertising content, moderate ads, and communicate moderation outcomes and policies to advertisers.

What you'll do

  • Develop and scale AI agents and ML models using multimodal, visual, and textual features across languages and countries.
  • Collaborate with engineers and scientists to train and deploy models, and write production code for ad moderation.
  • Define and measure relevant business metrics.

What they ask for

  • 3+ years of building models for business applications.
  • PhD, or Master's degree and 4+ years of experience in CS, CE, ML, or a related field.
  • Experience with patents or publications at top-tier peer-reviewed conferences or journals.
  • Programming experience in Java, C++, Python, or a related language; experience building ML models or algorithms for business applications.

Nice to have

  • Experience with AI Agents, multimodal ML models, transformers, computer vision, or vector representations.
  • Experience using Unix/Linux, professional software development, modeling tools, large-scale distributed systems, or statistics and measurement science.

Pay

USD 142,800.00 - 193,200.00 annually (base salary); USD 172,400.00 - 223,400.00 annually (base salary)

Tools

Java, C++, Python, Unix/Linux, R, scikit-learn, Spark MLLib, MxNet

AI focus

Build and deploy AI agents and ML models for multimodal ad-content understanding and moderation, including communicating outcomes and advertising policies to advertisers.

Model-written summary · the original posting is authoritative

First seen Oct 16, 2026 · Last verified Nov 5, 2026 (UTC)