Applied Scientist , Aws Healthcare-ai

Amazon Amazon · Big Tech · Mountain View, CA · Data Science

Senior Applied Scientist role at AWS Healthcare AI, focusing on developing and researching AI-driven clinical solutions to transform healthcare delivery. The role involves defining research directions, developing new ML techniques, and ensuring research translates into impactful products for clinicians and patients. Requires a PhD or Master's with significant experience in ML, NLU, deep learning, foundation models, and RL, with a strong publication record.

What you'd actually do

  1. contribute to the research and development of new, highly influencial AI applications that re-imagine experiences for end-customers (e.g., consumers, patients), frontline workers (e.g., customer service agents, clinicians), and back-office staff (e.g., claims processing, medical coding).
  2. define research directions, developing new ML techniques, conducting rigorous experiments, and ensuring research translates to impactful products.
  3. set the standard for excellence, invent scalable, scientifically sound solutions across teams, define evaluation methods, and lead complex reviews.
  4. collaborate with a team of scientists to invent novel, generative AI-powered experiences.

Skills

Required

  • NLU
  • deep learning
  • knowledge representation
  • foundation models
  • reinforcement learning
  • building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • 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

  • Unix/Linux
  • professional software development

What the JD emphasized

  • building models for business application experience
  • patents or publications at top-tier peer-reviewed conferences or journals

Other signals

  • building next-generation services
  • AI driven clinical solutions
  • transforming how clinicians interact with patients and document care
  • defining research directions
  • developing new ML techniques
  • ensuring research translates to impactful products