Chip Franzén is a Software Engineer at InnerPlant, where he designs and builds the company’s data and ML pipelines for agricultural sensing applications, with focus areas that include IoT, computer vision, and remote sensing. Prior to InnerPlant, he spent years applying machine learning to agriculture at companies including Granular and Indigo, working on land valuation, land cover identification using computer vision, spatial data pipelines, and MLOps for remote sensing-based agronomic models and inference APIs. At InnerPlant, he brings full-stack experience translating complex biological and geospatial signals into dependable, production-ready outputs that teams can use in real workflows. He holds a BA from Duke University and an M.Sc. in Data Science from Galvanize.
