Explainable AI in Malware Detection

I am seeking a professional with advanced expertise in machine learning and explainable AI, specifically for malware detection. This project focuses on the application and implementation of advanced ML algorithms, primarily BERT and Random Forest, to classify malware via API call sequences.

Key Responsibilities:
- Initial implementation of a malware detection model using BERT and Random Forest.
- Employing advanced ML techniques, including SVM, CatBoost, LightGBM, and LSTM, as necessary.
- Utilizing both Shapley values and LIME for achieving transparency and building trust in the model.

Ideal Skills and Experience:
- Extensive experience in machine learning and AI, with particular emphasis on BERT and Random Forest.
- Proficient in the use of Shapley values and LIME for model explainability.
- Prior experience in malware detection is highly desirable.
- Strong skills in classifier implementation via API call sequences.

This project aims to create a malware detection model that is not only effective, but also transparent and trustworthy, thereby enhancing the overall reliability of the detection process.