About the role
Effective use of AI will transform scientific research, but most lab data is stuck in silos. Scientists can't ask basic questions across their own experiments. Even the best tools can't help with what they can't see.
Labric builds the missing layer. We connect instruments, spreadsheets, and other data sources to a central platform, transforming data into useful visualizations and metrics. Scientists use it for cross-experimental analysis, visibility into colleagues' work, and application of the latest AI models.
We're working with companies, academic labs, and DOE national labs, and demand is outpacing our team. This is a rare chance to rebuild the tools the world's best scientists use to create tomorrow's technology
What you'll do
- Build core data infrastructure: ingestion, normalization, storage, indexing
- Ship across the stack (Python backend, TypeScript/Next.js frontend)
- Design schemas that make heterogeneous lab data queryable
- Work with scientists to turn domain problems into working software
- Own reliability and make good tradeoffs on quality vs. speed
About Labric
We started Labric after seeing the same problem everywhere. World-class research labs are running on outdated data infrastructure. Experimental context lives on post-its. Scientists email files to themselves for analysis. More time is spent wrangling data than doing science.
