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AI Referral Letter Triage Classifier

Alice Rossi

Full-time · Job · Chicago

About the role

Our mission is to cut the time specialists spend sorting incoming referral letters before they ever see a patient. Right now, referral coordinators read every letter by hand to decide urgency and department, which delays care for the patients who need it most. You will build a classifier that reads referral letters and predicts urgency tier and target specialty, trained on de-identified historical referrals and validated against coordinator decisions. We publish our methodology internally and expect you to read relevant clinical NLP papers and adapt findings rather than starting from scratch each time. You'll work alongside two NLP researchers and a clinical advisor who reviews edge cases weekly, in a small team that ships incrementally rather than waiting for a perfect model.

Responsibilities

  • Train and evaluate referral urgency classification models
  • Work with the clinical advisor to define labeling guidelines
  • Run error analysis sessions on misclassified referrals
  • Publish internal model cards for each release
  • Read and adapt recent clinical NLP research

Requirements

  • 3+ years working with NLP models in a healthcare or regulated setting
  • Experience with hugging face transformers and evaluation pipelines
  • Comfortable reading clinical documentation
  • Familiarity with de-identification workflows

Benefits

  • Remote-first with quarterly team offsites
  • Conference and paper submission budget
  • Health insurance stipend
  • Flexible hours across time zones

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face pandas

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Full-time

Level

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Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face pandas

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