Founding Machine Learning Engineer

Hard Technical Challenges The company sits at the edge of machine learning, biology, and experimental science. Some of the hardest problems you’ll work on include: Learning from sparse biology. Biological data is noisy, expensive, high-dimensional, and incomplete. How do we learn useful representations of cellular state from limited experimental data? Building models scientists can trust. Cells contain real biological structure: metabolism, regulation, signalling, transport, and stress response…