Directly Impact the Lives of Millions of People

It is exciting to know that your code will directly benefit millions of people worldwide. You will help shape the future of predictive medicine and set the expectations of this domain for years to come.

Forever Learning

Although our solutions touch millions of lives, we are just getting started on this journey. Our solutions are always evolving and adapting to meet new challenges. Our engineers shape the world with their keyboards similar to the way painters give life to a canvas with their brush.

Graduate Student Scholarships

We believe in the future generation of minds and feel it is our responsibility to empower the next wave of talent to create, learn, and be inspired. Retrace supports graduate students in computational mathematics, computer science, physics, and related fields. Please submit your CV, GPA, relevant coursework, and personal letter to [email protected]

Academic Grants

Retrace values science and feels it is our responsibility to help our community through academic grants. Retrace is proud to have already committed millions in grant money and products that have empowered thought leaders at leading institutions to continue to serve the community and help shift the paradigm of predictive medicine for the greater good of humanity. We would love to hear about your work and how you propose to incorporate AI into your clinical workflows. Please submit your CV, list of relevant publications, biography, and personal letter to [email protected]

Getting Hired

Selection & Interview Process at Retrace.

Phone Interview

We will cover your background, interests, and learn about your ideal team environment. We will also gauge your appetite for creativity and identify your specific domain expertise.


There is no better way to get insight into the way a person thinks than to work on real world problems with them. A short hackathon will be conducted that is designed to play upon the strengths of the future team member.

Navigating Data

The candidate might be given data that is intentionally contaminated. This type of challenge is common in world problems and the ability to identify and coup with mislabeled or underrepresented data is critical.