AI medical summaries for injury lawyers
You’ll be building tech to organize and normalize unstructured medical records, in order to answer highly detailed medical questions from our customers. These questions might look like, “when exactly was fentanyl administered during this patient’s hospital visit”, or “when was the patient turned over during their hospital stay”.
We have an LLM-based pipeline built out in Python as well as a Next.js UI. You’ll be working on improvements to our normalization pipeline, as well as major UI improvements. Most importantly, you’ll be helping drive the direction of the company as we strive towards our mission.
Our values:
Qualifications
Bonus Qualifications
We are a fully in-person company, must be willing to relocate to NYC. Able to sponsor TN or E3 visas.
98% of medical negligence victims go uncompensated, which we view as a moral failure of our justice system. We think fixing this is two-fold: solving hard technical problems to make the litigation process cheaper using LLMs, and solving market inefficiencies which artificially limit the supply of funding for medical malpractice cases. At Olive, we’re doing both.
We’ve hit $15k in monthly revenue in several weeks, but there’s so much more to do. We’re looking for a founding full stack engineer to join our team of two: a Harvard Law grad and a former Jane Street engineer who worked on finding and fixing market inefficiencies on their Options desk for 3 years.