Jobs 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.

Own and evolve ML infrastructure: maintain GCP via Terraform, manage IAM/RBAC, run CI/CD (CircleCI, GitHub Actions), administer workflow orchestration (Nextflow/Seqera, Argo, Kubeflow), manage experiment tracking (W&B, MLflow), build containerized environments and Kubernetes clusters, provision and debug GPU resources, write Python tooling, and deploy and monitor ML models in production.

Lead target validation for RNA editing therapeutics focusing on liver disease. Design, execute, and interpret in vitro studies, guide go/no-go decisions, mentor scientists, collaborate with Target ID and in vivo teams, and present data internally and externally.