Teams at Biohub

Design and build petabyte-scale data pipelines for genomic and imaging data, transforming public and proprietary datasets into AI-ready training data. Develop agent-based curation and quality-control systems, data cataloging tools, and reliable observable infrastructure. Collaborate with AI researchers and scientists to define data requirements and integrate diverse biological datasets while addressing performance, bandwidth, scalability, and scientific correctness.

Designs, prototypes, tests, and troubleshoots high-throughput single-cell screening and point-of-care medical devices. The role combines device engineering, cell biology, immunology, materials science, and reagent formulation. Responsibilities include developing controlled biochemical processes, handling biological specimens, validating assays, establishing test protocols, documenting work, and contributing to publications and patents. The engineer independently drives projects from proof of concept through prototype development in a collaborative laboratory environment.

Develop and scale frontier AI systems for biology, including foundation models, RL and multi-agent systems. Design model architectures, pre-training and post-training discovery pipelines, evaluation frameworks, and publish/open-source research with scientific collaborators.