Spring Discovery

Our engineering work falls into three broad buckets: 1) analyzing data from our experiments, 2) researching new computational approaches, and 3) building new technical infrastructure for our lab and our platform. We're very goals driven, setting goals at the 3-month, 1-month, and 1-week level, and we meet weekly to review/grade our goals. While we encourage clear accountability and ownership, we don't have strict roles and expect team members to be able to wear different hats and do a variety of different kinds of work in service of our mission. We also have very collaborative and cross-functional teams; our engineers work closely with our biologists to help design new experiments, analyze and troubleshoot data, and teach each other about biology and computer science.

We're building a platform to analyze vast amounts of rich biological data. This involves exploring, designing, and training machine learning models using more traditional as well as newer deep learning techniques. But machine learning is just one tool; it alone is not sufficient. Our work also involves thinking of, designing, and building many other workflow and visualization tools to give humans superpowers – we want to empower our scientists and automate their workflows and enable them to analyze data at consumer internet scale.