ML XGBoost Python Migration to C++

I am looking for a developer to finalize the migration of a Machine Learning simulator that uses the XGBoost algorithm, currently developed in Python, to C++. The migration should be done using the MLB (Machine Learning Base) library. The main goal of this initiative is to improve the execution performance of the simulator and enable direct integration with legacy systems written in C++. The Python version is already fully operational, with all pipelines working as expected; the focus of the migration is to adapt the simulation logic to the new language.

Specific project objectives include:

Migrate the inference pipeline based on a pre-trained XGBoost model from Python to C++.

Fully preserve the preprocessing logic, simulator structure, and the accuracy of the results.

Conduct performance benchmarking and thorough unit testing between the Python and C++ versions to validate the optimization.

Ensure complete compatibility with the current model's input and output interfaces, maintaining operational continuity.

Essential Technical Requirements:

Proficiency in both C++ and Python.

Hands-on experience with Machine Learning, including model handling, feature engineering, and debugging.