Research Scientist – Large Tabular Models (LTMs)
mid$160K – $250K
via Ashby
About this role
Location: Mountain View, CA (On-site)
OVERVIEW
Most of today's generative AI is built for text, images, and video.
Enterprise data isn't.
The world's most valuable data lives in tables: customer records, transactions, financial systems, telemetry, operational data, and business workflows. Today's generative AI stack wasn't designed to learn efficiently from this kind of information.
At Granica, we're building Large Tabular Models (LTMs)—foundation models that learn natively from structured and relational enterprise data.
Our research is led by Prof. Andrea Montanari (Stanford) and focuses on one central question:
How can we build generative AI that learns efficiently from tabular data?…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: pytorch
2
Level fit
This role is mid-level. We check your trajectory against it.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is based in a specific location. We weight your proximity and willingness to relocate.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
pytorch
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