We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through each step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics.
We're hiring across the following areas:
* Software Engineering: Program Lead, Product, Product - Quantitative Modeling, Bayesian, Program Synthesis
* Research: Applied Category Theory, Analytic Learning Algorithms
* Domain Experts - Valuation, Quantitative Default-Probability, or Interest Rate Prediction Models: to collaborate on use cases, from opportunity validation through production
Find out more, and apply at: https://planting.space/joinus/