Machine Learning Engineer (Research)

New York, NY or Remote /
Engineering /
Who we are
Onehot Labs is a healthcare technology startup harnessing machine learning and natural language processing to build products that make medical billing and reimbursement more efficient and cost-effective. By reducing human error, eliminating paperwork and streamlining medical billing processes, our solutions help doctors spend more time taking care of patients and allow patients to spend less time worrying about their medical bills. We are innovators, experimenters, lifelong learners, and free thinkers who strive to have a positive impact on the world around us and are working together to create a company that we all want to work at. Our pioneering tech is in use in all 50 states, and we review clinical documentation for over 1,000,000 unique patient encounters each week (80% of which we automate using our machine learning systems!).

The Opportunity.

Ready to participate in cutting-edge research to develop solutions for real-world, large-scale problems in healthcare? Our company works on a huge supervised text classification problem and has amassed over 250 million labeled medical encounters. We read doctor’s entries into Electronic Medical Records (EMR) and convert the text into 15+ mutually exclusive labels that are needed to fill out insurance paperwork.

We are looking for researchers to help us push the boundaries of what is possible when applying state-of-the-art transformer-based approaches to massive, labeled clinical data. This will touch on research problems that involve improving the accuracy of text classification models to real-time text suggestion/summarization for doctors (think reading 2 pages of nurse’s notes and then writing a summary paragraph that a doctor can sign off on). The research will also push into multimodal settings where we will need to involve images (such as x-rays) and/or information extraction from scanned documents.

The primary objective of this research position is to foster academic collaborations with students who would like to productionize their research on real-world, clinical applications. The position is well paid and intended to allow for ultimate flexibility and autonomy beyond traditional “jobs” on aspect such as duration, time commitment and working location. The topics student researchers would work on are meant to be open-ended and exploratory – focused on exploring the art of the possibility given recent advancements brought about by transformers.

Who you are

    • The ideal candidate will combine research experience with a strong desire to put research into production models used by doctors in millions of encounters every week.
    • Currently enrolled in a graduate program in Computer Science, Linguistics, Statistics, Applied Mathematics, Operations Research or a related technical field.
    • Experience using Transformers across text-based modalities
    • Experience with Python
    • Large-scale model training experience on cloud infrastructure (GCP is a plus)
    • Have an imagination, ambition, and intense curiosity. Be innovative. Skilled in communication.
    • Ability to thrive in a dynamic and fast paced environment.
Why join Onehot Labs?
-Rare opportunity to join a profitable startup.
-Startup feel + “big company” benefits, like competitive compensation! Full time employees receive 401k, Health, Dental, Vision, HSA, FSA, Commuter Benefits & more!
-Unlimited PTO and flexible remote schedule so you can take the time you need.
-Work on a dynamic range of projects that you couldn’t get at a “big company”.
-Together we create a company culture that we all want to work at.
-Love coming to work - though we are mostly remote we have an office in Flatiron, the heart of New York City, and a team out near Denver, CO
-Learn more about us and the core values that drive Onehot Labs.

Equal Opportunity Employer
Onehot Labs is committed to building a diverse and inclusive company that celebrates and develops individuals of all backgrounds. We are an equal opportunity employer and encourage all applicants.