About Labric
About Labric 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. Backed by Y Combinator.
About the role
Competitive base with flexible salary/equity split. ($140K - $200K, 0.50% - 2.00%)
What they're looking for
- 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
- Strong in Python and TypeScript
More about this role
- 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
- Strong in Python and TypeScript
- Know databases deeply (not just how to use them, how they work)
- Comfortable independently solving problems end-to-end
- Curious about science and how labs actually operate
- CS degree or equivalent
- [optional] Have experience with scientific data, Django, Next.js, GCP, SQL, early-stage startups
Competitive base with flexible salary/equity split. ($140K - $200K, 0.50% - 2.00%)
Work visas will be considered on a case-by-case basis.
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