Our Mission
At DeepScribe, everything we do is focused on our mission: to bring the joy of care back to Medicine. Our goal is to empower physicians with the tools they need to improve both efficiency and efficacy, and to improve patient outcomes by increasing the trust and understanding they have with their physician. Our first product, an AI medical scribe, mimics near-human level intelligence by parsing through medical conversations and creating detailed visit summaries for physicians. With this ambient scribe technology, we have been able to save physicians up to 3 hours a day. 
 
What you’ll do
Our AI-Scribe has recently gone viral in the field of healthcare, leading to rapid growth in every aspect of the business - customer-base, product offering, team, and healthcare footprint. We’re going from a radical idea to a mature offering, which means redesigning, rethinking, and rebuilding to enable this next chapter. You’ll work with the largest and fastest-growing dataset of physician-patient conversations to improve our current models, work with the product team to develop ML-powered features, and mentor/guide/grow our ML team.

Requirements

  • BS, MS, Ph.D. in Computer Science, Data Science, Statistics or related discipline, or equivalent industry experience
  • Research work, publications, or work experience in a related domain or problem space (personal projects don't count)
  • Strong foundation in Python, Java, C++, or similar
  • Experience with common ML frameworks such as PyTorch or Tensorflow
  • Solid theoretical understanding of machine learning
  • Strong NLP and ML fundamentals (LSTMs, NER, Word Embeddings, Transformers, etc)

Your Experience

  • Modifying and optimizing our current NLP models
  • Tune models to the constant inflow of conversational data
  • Prototyping, building, and deploying new models to serve as the core of new product features
  • Data structuring and cleaning
  • Working with our infrastructure team to get your models into production
  • Demoing your awesome work to the leadership team

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