Hiring medical students to help with AI company ($35/hr) - Remote

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About us
Layer Health is a stealth AI startup recently spun out of MIT, revolutionizing clinical documentation by leveraging the power of large language models. We are building an AI layer that will radically speed up and improve the quality of extracting and synthesizing information from medical records, with the mission to reduce friction everywhere in healthcare, power the future of precision medicine, and ultimately improve patient outcomes. Our diverse founding team brings expertise across machine learning, large language models, medicine, and human-computer interaction.

We’re seeking exceptional medical students who are interested in working at the forefront of Artificial Intelligence and Machine Learning, as a part-time independent contractor.

Job Description
We’re looking for medical students, who will work as independent contractors, to help annotate and label medical notes to evaluate our large language model algorithms.

You can expect to:
  • Annotate medical notes, given specific guidelines, under the supervision of a board-certified physician
  • Review and annotate machine learning outputs
  • Work with ex-MIT/ex-Google engineers to help improve machine learning models
  • Gain an appreciation for the opportunities and current limitations of machine learning

We look for candidates who are:
  • Detail-oriented
  • Able to work independently, cooperatively, and collaboratively as a team member
  • Currently living in the United States
  • Authorized to work in the United States and able to pass a background check.
  • Ideally based on the East Coast (Eastern Standard Time)
  • Already enrolled in a medical school in the United States
  • Well versed in medical terminology and clinical reasoning, either through previous experiences with clinical notes (medical research, scribe, etc.), or have already started clinical rotations

Commitment & Compensation:
  • Ability to work on an as-needed basis, ~10 hours / week
  • $35/hour

Interested candidates should email a copy of their CV to [email protected]

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