TL;DR Davis is hiring a Founding Data Engineer to build the data behind our foundation model, trained from scratch to generate buildings as geometric graphs.
You will own the data end to end, from raw floorplans and synthetic generation to a canonical representation, curation, large-scale pretraining and the ablations that tell us which data actually moves the model.
Here the dataset is part of the algorithm.
Today developers coordinate four to five fragmented stakeholders over weeks or months.
Soon they will need only one: Davis.
We turn every input that shapes a development decision into decision-ready outputs: investor-grade feasibility studies, investment analysis, and architect-certified designs, delivered in days.
Every stage pairs our proprietary AI systems with expert review, so velocity never comes at the cost of reliability.
We closed a $5.
5M pre-seed co-led by Heartcore Capital and Balderton Capital, with Yellow, Evantic and Entrepreneur First, alongside angels from the founding teams of Spacemaker, Black Forest Labs, Hugging Face, Supabase, Cleo and Spore Bio.
We already work with leading developers and expect to support hundreds of projects over the coming year, deepening our research, our hiring, and our coverage of the development process end to end.
The RoleYou will own the data our foundation model learns from, a model we train from scratch to generate buildings as geometric graphs.
Part of the corpus comes from real floorplans as images and PDFs that have to become clean, standardized graphs.
A large part will be synthetic, procedurally generated building graphs, geometry and rendered floorplans, with controlled variation in style, scan noise, annotations and furniture, each kept with its ground-truth graph automatically.
You will think about the whole loop, from raw and synthetic data to a canonical structured representation, curation.