The Role: We are seeking talented, hard working associates to join our Machine Learning team for a fixed-term role.

At BigHat Biosciences, we’ve re-framed antibody drug development as an iterative, machine learning–driven, multi-objective optimization problem. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom data management and orchestration layer to automatically update and deploy the latest models. This makes development of complex, net-gen therapeutics ‘trivially parallelizable’, at a pace which only accelerates as we develop better ML tooling.

As an ML Research Fellow you’ll work on developing novel ML models as well as helping with routine ML support of our ongoing therapeutics programs. Applications include multi-modal models of antibody biophysical properties, de novo and structure driven protein design, better protein language models, and active learning and bayesian optimization methods for embedding these models in our design-build-test loop, amongst many others. You’ll be mentored by an experienced ML scientist from our team and work closely with an interdisciplinary team of engineers, wet-lab scientists and drug developers to ensure your work is relevant for active drug development programs.