Research Engineer – Machine Learning Systems
mid
via Ashby
About this role
Location: Mountain View, CA (On-site)
OVERVIEW
Most of today's AI is built for text, images, and video.
Enterprise data isn't.
At Granica, we're building Large Tabular Models (LTMs)—foundation models that learn natively from structured and relational enterprise data.
Our research, led by Prof. Andrea Montanari (Stanford), explores how generative AI can learn more efficiently from enterprise data through better representations, data selection, augmentation, and compression.
As a Research Engineer, you'll bridge research and production—turning new ideas into scalable machine learning systems that power the next generation of enterprise AI.
This is not an LLM application engineering role.…
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: c++, 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.
c++pytorch
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