Applied Machine Learning Engineer
- Silicon Valley, CA, United States
- Google Cloud
Spring is accelerating the discovery of therapies for aging and its related diseases. Machine learning and data science are at our core, and we're building a rare computational team that works closely with our biologists, together fighting disease.
We're looking to add to our early team with a senior applied data scientist/machine learning engineer to help lead the analysis of rich biological data to advance discoveries of therapies. The ideal candidate would be somebody who's mature, is comfortable with open-ended and ill-defined problems, and can communicate the details of nuanced analysis effectively.
- Experience. You have 3+ years of real-world experience in software development in a collaborative setting.
- Tends towards ownership. You do anything necessary to solve the problem at hand.
- Maturity in face of ambiguity. You help define questions instead of just answering them. You work to resolve ambiguity — and you're comfortable making decisions when it remains.
- Crisp communicator. You excel at crisp, concise written or spoken communication. You love learning and teaching others in a cross-functional team (we're biologists, computational folks, and more).
- Driven by impact. You're most motivated when working on a problem of important consequence, no matter what's necessary to do so.
About Spring Discovery
We’re building a platform powered by machine learning to understand the biology of aging and power the discovery of therapeutics.
Aging is the single greatest risk factor for the most detrimental diseases on Earth — cardiovascular disease, neurodegenerative disease, pulmonary disease, cancer, muscle wasting, and more — and drugs that slow the biological damage accumulated while aging have the potential to reduce the incidences of these diseases, possibly simultaneously. We believe that in the not-too-distant future, the discovery of therapies for aging will provide some of the most effective tools in history for reducing our burden of disease and extending our healthy lifespan.
Our mission is to dramatically accelerate the realization of that future.
We value speed of execution, and, more importantly, speed of learning. We set ambitious goals, and intend to make progress every single week towards it. We know that means working hard, but healthily so – this is an epic mission with a long road ahead and we're just getting started.
A critical aspect of our operation is deep collaboration between scientific and computational teams. We don't expect engineers to come with a background in biology, just as we don't expect our biologists to be experts in software engineering. We do expect our teams to work respectfully and closely, learning together every day.
- Google Cloud
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