Develop and deploy scalable, production-ready AI and machine learning models for protein, antibody, and broader drug discovery. Collaborate with AI scientists, engineers, and drug discovery experts to translate research concepts into robust systems, support large-scale model training, and deliver measurable impact in life sciences and healthcare.

Develop and apply deep learning models for protein and antibody structure, sequence, and property modeling. Train and evaluate GPU-based models using PyTorch, contribute to computational protein design research, analyze biological and biophysical datasets, document findings, and communicate progress with interdisciplinary scientists and engineers.

Build and operate ML infrastructure for large-scale biological foundation models: dispatch distributed training across multi-cloud GPU clusters, deploy high-throughput storage, implement evaluation and experiment-tracking tooling, and integrate training with telemetry and checkpointing systems.