Teams at Deep Genomics

Build and optimize engineering infrastructure to bridge fast-paced ML research and production. Refactor and harden experimental code, implement/train/evaluate PyTorch models, rigorously test and profile systems for correctness and performance, and balance rapid iteration with pragmatic architectural decisions to enable production-ready research.

Execute amplicon sequencing and NGS library prep, perform PCR/qPCR/ddPCR and nucleic acid extraction, run QC (TapeStation, Qubit, qPCR), operate Illumina NextSeq and liquid handlers, maintain ELN documentation, and collaborate with computational and therapeutic teams to generate high-quality experimental data supporting RNA therapeutic discovery.

Lead research and design of large-scale Biological Foundation Models (BioFMs) using genomic and single-cell data. Develop novel architectures and pretraining paradigms, implement and train models at scale, collaborate with biologists and drug developers, mentor junior researchers, and publish findings in top-tier venues.