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Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific…
Designs and builds petabyte-scale data pipelines to ingest, transform, and prepare heterogeneous biological datasets (genomics, imaging, metadata) for AI model training, ensuring scalability, reliability, and scientific accuracy to accelerate disease research.
Staff AI Infrastructure Engineer responsible for the reliability, scaling, and incident response of large-scale multi-GPU clusters running Slurm on Kubernetes, debugging deep failures across storage, networking, and GPU compute layers at a non-profit biology research lab.
Designs and implements secure systems for AI-driven biomedical research, integrating security into AI compute infrastructure and automating threat detection for a cutting-edge lab.
Design AI-ready data representations for biological imaging, guiding how frontier models learn from raw images and other modalities to accelerate disease research.
Lead cross-functional teams to plan and deliver cutting-edge imaging and AI projects that accelerate scientific discovery and disease research.
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