Python ML Engineer to Build Agricultural Intelligence Platform

We are StrataAg Technologies(Canada head-quarted) is looking for a freelance ML/software engineer to build our platform from the ground up from zero to MVP and potentially through to production. The system pulls in weather forecasts, commodity market data, and farm financial data, and combines them into a single risk score at the per-acre level. The weighting between those three inputs shifts depending on the time of year and crop cycle. Outputs include a confidence score so recommendations are never just a binary yes or no You'll own: The full stack. Data ingestion and cleaning, database design, core scoring and decision logic, backend API, and a simple frontend for farm operators to view and understand their risk outputs. The farmer-facing interface doesn't need to be complex, but it should be intuitive enough that someone running a farm operation can open it and immediately understand what they're looking at. You're the right fit if: You've built a multi-input scoring or risk system before and are comfortable making independent modeling decisions. Quant finance, insurance, actuarial, or credit backgrounds translate well, but other experience in ML/Data Science are welcome. You've shipped something that ran in production and can take a well defined problem and run with it independently. This isn't the right project if: You prefer inheriting existing infrastructure, need a defined ticket queue to operate, or your default approach to every problem is deep learning before considering simpler solutions.