Machine Learning Engineer • Software Engineer • Security-Oriented Builder
Building explainable, deployable AI systems with real-world impact.
I'm a machine learning engineer with a background in computer engineering and software development. I specialize in real-time detection systems, LLM-based assistants, and AI-integrated platforms. I bring together MLOps practices, deployment experience, and a strong interest in cybersecurity and applied ML. Open to roles across AI, applied research, and full-stack ML engineering.
Production-ready DoS/DDoS attack detection using One-Class SVM with SHAP explainability. Includes FastAPI REST API, Streamlit dashboard, and full Docker deployment.
Built a retrieval-augmented generation (RAG) system for legal documents. Uses Qdrant + FastAPI backend and OpenAI embeddings to deliver accurate semantic responses.
🔗 Repo
A productivity platform for students with scheduling, task boards, and learning trackers. Built with Next.js, Zustand, and Tailwind.
🔗 Repo
Languages & Frameworks:
AI/ML Tools:
scikit-learn • SHAP • OpenAI API • PyTorch • Autoencoders • Anomaly Detection • RAG Systems
DevOps & Infra:
Docker • Render.com • Git • Streamlit • Supabase
