• Design, implement, and train novel deep learning architectures for TCR–pMHC specificity prediction. • Extend and adapt advances in protein language models, structure prediction, generative modeling, and representation learning to the immune receptor setting. • Leverage and influence scalable training infrastructure to support large-scale model development and experimentation. • Lead rigorous benchmarking and evaluation strategies to ensure models are scientifically sound and practically superior. • Translate biological principles of T cell recognition into principled modeling decisions. • Influence large-scale experimental data generation to maximize modeling leverage and long-term performance gains. • Evaluate emerging ML advances and determine when and how to incorporate them into Adaptive’s modeling roadmap. • Shape the long-term technical direction of machine learning in immune receptor prediction across the organization. • Partner with computational biology, immunology, translational, and engineering teams to ensure models are capable, scalable, reproducible, and aligned with therapeutic and diagnostic goals. • Clearly communicate complex modeling insights to scientific leadership, executives, and external partners. • Contribute to intellectual property development and high-impact publications.