Senior Applied Scientist, Funnel Agentic Intel

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

This role focuses on building and evaluating agentic AI systems for Amazon Ads. The agent will understand advertiser intent, reason about campaign strategy, and execute actions across the Amazon Ads portfolio. Key responsibilities include designing and building multi-step agentic workflows, invoking tools, and taking autonomous actions. The role also involves defining evaluation frameworks for agent reliability, correctness, and safety, analyzing agent behavior through data analysis and A/B experimentation, and partnering with cross-functional teams to ship end-to-end agent experiences at scale.

What you'd actually do

  1. Design, build, and evaluate agentic systems that plan multi-step workflows, invoke tools, and take autonomous actions across Amazon Ads products on behalf of advertisers.
  2. Define evaluation frameworks and benchmarks for agent reliability, correctness, safety, and advertiser satisfaction.
  3. Analyze agent behavior through deep data analysis and rigorous A/B experimentation to identify failure modes, measure effectiveness, and derive business insights.
  4. Partner with engineers, product managers, and UX designers to ship end-to-end agent experiences that are scalable, efficient, and reliable at Amazon scale.

Skills

Required

  • building machine learning models for business application
  • PhD or Master's degree and 6+ years of applied research experience
  • programming in Java, C++, Python or related language
  • neural deep learning methods
  • machine learning

Nice to have

  • modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • large scale distributed systems such as Hadoop, Spark etc.

What the JD emphasized

  • building intelligent agents that reason, plan, and act across complex advertising workflows
  • agentic AI
  • large language models
  • agentic systems
  • multi-step workflows
  • autonomous actions
  • agent reliability
  • agent correctness
  • agent safety
  • agent behavior
  • AI-native interface

Other signals

  • building AI-powered agents
  • reasoning over campaign strategy
  • executing across the full Amazon Ads portfolio
  • automating time-consuming tasks
  • providing data-driven recommendations
  • shaping how millions of advertisers interact with Amazon Ads