Jobs in Berkeley, CA

About the role

We’re looking for someone who can build and productize our virtual immune system! We work directly with members to collect fully paired data spanning clinical records / real world data along with multiomic data spanning assays from WGS, scRNA (5’/TCR/BCR, 3’/ATAC), proteomics, metabolomics, reactomics, and beyond - all over time as member’s health changes. You’ll be focused on leading our efforts to handle all of the multiomic data we have, and then utilizing it to power AI scientists, AI models, and other analyses that we will run internally and in partnership with other researchers. You should naturally handle highly ambiguous situations with tenacity, discovering paths forward using both internal and external feedback. The work spans several domains - biology, AI, infrastructure, and product development. You should have demonstrated a high capacity to learn quickly, is paranoid about data quality and rigor, and has a track record of demonstrating great judgement. At the moment, the role emphasizes individual contribution, though over time as the team grows, the candidate will have the option to lead and mentor. We’re looking for someone who can build and productize our virtual immune system. We work directly with members to collect fully paired data spanning clinical records/real-world data along with multiomic data—including assays from WGS, scRNA (5’/TCR/BCR, 3’/ATAC), proteomics, metabolomics, reactomics, and beyond—all over time as members’ health changes.

What you'll bring

• PhD or equivalent experience in Computational Biology, Bioinformatics, Systems Biology, Computer Science, or a related quantitative field.
• 5+ years of industry experience in computational biology
• Deep expertise in analyzing multiomic datasets, including single-cell genomics (scRNA, ATAC, TCR/BCR), bulk sequencing, or proteomics/metabolomics.
• Demonstrated track record of developing machine learning or deep learning models for complex biological data and biological target/feature discovery.
• Strong software engineering and data infrastructure capabilities for productizing models and pipeline architectures.
• Domain expertise in human immunology, autoimmune diseases, or systemic inflammatory response modeling.
• Experience working with electronic health records (EHR), longitudinal clinical datasets, and real-world data integration.
• Experience building foundation models or generative AI architectures tailored for biological multiomics.
• Proven ability to lead technical teams or cross-functional research initiatives in high-growth startup environments.
• preferably on a small team.

Benefits