Senior Python Machine Learning Engineer for DNS Content Classification System

We are looking for a Senior Python Machine Learning Engineer to develop a complete proof-of-concept system for automatic web content classification focused on parental protection. The project combines Machine Learning, NLP, DNS technologies, and Linux. We already have a detailed project specification, system architecture, methodology, and implementation plan. We need an experienced engineer to implement the technical solution. Main Responsibilities Build a labeled dataset from the UT1 blacklist dataset. Implement a domain-name classifier using character n-grams. Implement HTML content extraction and preprocessing. Develop text classification models using TF-IDF and Scikit-learn. Compare multiple models (Random Forest, SVM, Naive Bayes or similar). Design and implement a hybrid multi-stage classification pipeline. Integrate the classifier with a BIND9-based Protective DNS (PDNS) server. Automate testing and evaluation. Produce clean, well-documented Python code. Use Git throughout the project. Required Skills Python (advanced) Scikit-learn Machine Learning Natural Language Processing (NLP) BeautifulSoup Requests Pandas Linux Docker DNS / BIND9 Git Nice to Have Experience with web classification Experience with DNS infrastructure Cybersecurity background Experience with text classification Experience with Linux servers Deliverables Complete Python source code Dataset construction scripts Training and evaluation pipeline Performance metrics Docker environment BIND9 configuration Documentation explaining the implementation Important Code quality is very important. The implementation should be modular, well documented, reproducible, and follow software engineering best practices. Please include in your proposal: Similar Machine Learning projects you have completed. Experience with Python and Scikit-learn. Experience with Linux and BIND9 (if any). Your estimated timeline. Your hourly rate.