Senior Applied ML Engineer specialising in forecasting, calibration and tabular data.

We need an applied ML engineer to test whether specialist correction models can improve forecasts from systems such as FutureSearch. You will: - Audit existing backtests for data leakage. - Build chronological and untouched test sets. - Train correction models using FutureSearch outputs and structured data. - Compare FutureSearch against FutureSearch plus correction. - Report accuracy, calibration and confidence intervals. - Produce a reproducible, investor-ready case study. You should have experience with: - Python and scikit-learn - Tabular or time-series forecasting - Probability calibration and Brier scoring - Leakage-safe backtesting - Logistic regression, Ridge and gradient boosting LLM forecasting, real estate, credit or SEC-data experience is helpful. To apply, send a relevant project, your proposed testing approach, availability and rate.