Sr. Applied Scientist, Aws Healthcare-ai

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

Senior Applied Scientist at AWS Healthcare AI focused on developing and researching AI-driven clinical solutions to transform patient-clinician interaction and care documentation. The role involves leading research, developing new ML techniques, and ensuring research translates into impactful products, with a focus on generative AI experiences.

What you'd actually do

  1. lead pioneering research and development of new, highly confidential 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. defining 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. guide a team of scientists to invent novel, generative AI-powered experiences.

Skills

Required

  • building machine learning models for business application experience
  • 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

  • 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

  • highly confidential AI applications
  • novel, generative AI-powered experiences
  • new ML techniques
  • rigorous experiments
  • scalable scientific solutions
  • define evaluation methods

Other signals

  • AWS Healthcare AI
  • 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
  • leading complex reviews