Applied Scientist Iii- Recruiting AI Agents, Recruiting Agents & Candidate Voice

Amazon Amazon · Big Tech · Seattle, WA · Human Resources

This role focuses on designing, implementing, and deploying AI-powered agentic solutions for Amazon's talent acquisition process. The scientist will leverage LLM and GenAI technologies to create conversational AI agents that guide candidates through the hiring journey, and will develop evaluation frameworks to measure agent effectiveness and user experience. Collaboration with cross-functional teams and staying current with agentic AI research are also key responsibilities.

What you'd actually do

  1. Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability.
  2. Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey.
  3. Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions.
  4. Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals.
  5. Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing.

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

  • agentic solutions
  • conversational AI agents
  • LLM and GenAI technologies
  • evaluation frameworks
  • agent effectiveness
  • candidate experience
  • system scalability
  • hiring process
  • autonomous agent architectures

Other signals

  • design and architect AI-powered agentic solutions
  • implement and deploy conversational AI agents
  • develop rigorous evaluation frameworks to measure agent effectiveness
  • integrate agentic solutions into Amazon's candidate-facing platforms