Spring Discovery | Machine Learning Engineers | Full-Time | SF Bay Area | ONSITE preferred (REMOTE possible – let's discuss)
Spring Discovery is building a machine learning platform to accelerate the discovery of therapies for aging. Why? Simply because aging is the single greatest risk factor for the most detrimental diseases we know of – cardiovascular diseases, neurodegenerative diseases, even COVID-19 (see our work on this in [1] below). By understanding and treating the biological damage accumulated as we age, we can find powerful new therapies for fighting disease and living not only longer, but healthier lives.
Over the past few decades, an unignorable amount of evidence has piled up from the best labs in the world showing that this is possible [2]. However, the research, while promising, has been frustratingly slow. We’re leveraging the power of machine learning to dramatically improve the experimental process and we believe this approach has the potential to unlock a whole new class of therapeutic discoveries.
We're fortunate to have great backing from top investors, including General Catalyst, First Round, Laura Deming's Longevity Fund, Felicis, Caffeinated Capital, Sam Altman, and more. And our advisory board includes both world leaders in aging research and senior pharma execs.
We have a great early team of senior engineers (ex-Google, Khan Academy, CZI, Freenome) collaborating tightly with leading scientists in the field. But we need help to continue scaling out our ML approaches and platform. We’re looking for experienced ML engineers / applied researchers who would enjoy working on helping us answers on large biological datasets. Yes, you belong even if you don't have a bio background — we're a cross-functional team. (Although of course biology experience is a plus).
If this sounds interesting to you, head on over to <a href=" or email me directly at benkomalo+REDACTED_EMAIL.
[1] <a href="
[2] <a href="
Ask HN: Who is hiring? (September 2021)