Machine Learning Engineer Needed to Build Gold Price Prediction Model (Time‑Series Forecasting)

I’m looking for an experienced Machine Learning Engineer to develop a gold price prediction model using historical market data. The goal is to build a reliable time‑series forecasting system that can generate short‑term and medium‑term predictions. Scope of Work: • Collect and clean historical gold price data (spot and/or futures) • Engineer relevant features (technical indicators, volatility measures, macro inputs) • Build and compare multiple forecasting models (LSTM, GRU, Prophet, XGBoost, etc.) • Evaluate performance using proper metrics (RMSE, MAPE, directional accuracy) • Provide clear documentation and explanation of model performance • Deliver a working Python script or notebook with reproducible results • Optional: lightweight dashboard for visualization Requirements: • Strong background in machine learning and time‑series forecasting • Experience with Python, pandas, NumPy, scikit‑learn, TensorFlow/PyTorch • Ability to explain model decisions and provide recommendations • Experience with financial or commodity data is a plus Deliverables: • Clean dataset • Final trained model • Codebase with documentation • Prediction outputs + evaluation report This is a one‑time project with potential follow‑up work.