Principal Machine Learning Scientist

Adaptive Biotechnologies is seeking a Principal Machine Learning Scientist to lead the development of deep learning models for TCR–pMHC specificity prediction.

In this role, you will leverage a large and growing proprietary dataset to design, train, and evaluate models that predict interactions between T cell receptors and peptide–MHC complexes. Your work will focus on developing new approaches that integrate sequence and structural information and rigorously testing their performance in practical settings.

You will work closely with computational scientists, immunologists, and machine learning engineers across the organization. The team brings together expertise in immune biology, experimental assay development, and large-scale machine learning, with access to proprietary immune receptor datasets, shared GPU infrastructure, and engineering support for model development and training.

This role sits at the intersection of modeling and experimental data generation. As model results highlight gaps in available data or suggest new experimental directions, newly generated datasets can provide additional signal for improving and validating the models.

Models developed in this role contribute directly to diagnostic and therapeutic initiatives both within Adaptive and through external partnerships. This position offers the opportunity to advance predictive modeling of immune receptor specificity while seeing those advances translated into meaningful clinical and commercial applications.