Anagenex

We are a seed stage biotechnology company building a novel platform for drug discovery focusing on difficult targets. Machine learning has struggled in early stage drug discovery efforts because most of these efforts do not have enough data for the models to parse. Our technology solves the data problem with massively parallel biochemistry in the form of DNA Encoded Libraries (DELs), allowing us to analyze 100-1000x more compounds compared to traditional approaches. By feeding our algorithms with this data we can identify better compounds faster than competing solutions. We recently closed a substantial seed investment (2+ years runway) and are assembling a highly interdisciplinary team of both bench and computational scientists. Come help us build the future of drug discovery! Lead ML Engineer: We are looking for our first computational hire who in time will help build and manage this team. This person will be driving technology choices, designing and building data architectures and building models. These systems will take in raw experimental data as well as other information from lab instruments and integrate that data into models predicting several biochemically relevant properties. Familiarity with current ML and data pipeline tools is a must. We favor python, but aren’t dogmatic. Computational Chemist: We are looking for a computational chemist to create a cutting edge drug discovery toolchain. We strongly favor open platforms such as RDKit but are open to alternatives that maximize performance. This person should be familiar with traditional SAR, structure based drug discovery, ADME prediction and have some exposure to more recent ML applications to drug discovery. These roles are both asking a lot, and correspondingly we offer strong equity and competitive compensation. The roles are also a unique opportunity to build systems correctly from the ground up to solve a really important problem! Odds and ends: Interview process is generally a few phone/video conversations and some small practicum work, but is adapted to the individual at this stage of the company. Onsite is expected to eventually be in SF, but we are launching a Boston location for our lab operations. Of course, given the pandemic is hybrid/remote for the time being, and might continue to be longer term.