Sr Applied Scientist, Responsible AI

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

This role is for a Sr. Applied Scientist on Amazon's central Responsible AI team. The mission is to advance the science and practice of Responsible AI (RAI) to enable builders to deploy AI solutions to high standards. The scientist will understand RAI issues, define strategies, solve open problems, publish research, help develop the team, and liaise with stakeholders. Requires a PhD or Master's with 6+ years of applied research experience, and experience with deep learning and ML.

What you'd actually do

  1. understand in depth the technical and scientific issues related to RAI, including controllability, security, privacy, safety, veracity, robustness, fairness, explainability, transparency, and governance
  2. help define the strategies, priorities and metrics for RAI
  3. solve open problems in RAI to unblock traditional, generative and/or agentic AI use cases and solutions, publishing as appropriate
  4. help develop our team
  5. liase with internal and external stakeholders, including the academic community, on issues related to RAI

Skills

Required

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

Nice to have

  • Experience prioritizing and delivering projects on time in a fast-moving environment
  • Passion for responsibly building and operating complex AI/ML systems, with consideration for controllability, privacy, security, safety, veracity, robustness, fairness, explainability, transparency, and governance.
  • Excellent verbal and written communication skills, with demonstrated ability to synthesize large amounts of complex data and communicate complex concepts effectively to internal and external stakeholders.
  • Publication record on issues in responsible AI or related to responsible AI

What the JD emphasized

  • Responsible AI
  • controllability
  • security
  • privacy
  • safety
  • veracity
  • robustness
  • fairness
  • explainability
  • transparency
  • governance
  • publication record on issues in responsible AI or related to responsible AI

Other signals

  • Responsible AI
  • controllability
  • security
  • privacy
  • safety
  • veracity
  • robustness
  • fairness
  • explainability
  • transparency
  • governance