Founding Machine Learning Scientist

About Tabula

Tabula is building an AI-first therapeutics company.

We are starting with bacteriophages, natural predators of bacteria, and building the models and experimental systems needed to design better therapies for hard-to-treat infections. The immediate problem matters on its own. Antibiotic resistance is a large and growing global problem, and new approaches are badly needed. But we also think this is the beginning of something broader.

Most biotech companies are mostly biologists with a small computational team attached. We think that model is going to look dated. Our view is that drug and therapy discovery will become much more computational over time, and we are building Tabula around that belief from day one.

Two things make this a particularly interesting problem for machine learning. First, we own our data generation loop. We are not just consuming static datasets and hoping they are good enough. We can generate new data, learn from it, and improve the system over time. Second, phages are one of the rare places in biology where the path from model output to human impact can be unusually short. We picked this area in part because, relative to most of biotech, the feedback loop to real-world use is fast.

One way to describe what we are doing is simple: we are using machine learning to help