Open to entry-level ML, AI & data roles
Machine Learning Engineer · Applied AI Developer
Computer Science graduate building end-to-end solutions across RAG, fraud risk, demand forecasting, and computer vision—with APIs, testing, monitoring, and deployment in the loop.
I am Md. Alif Hossen, a Computer Science and Engineering graduate focused on machine learning, applied AI, and data-driven applications.
I build Python-based end-to-end systems spanning data pipelines, model validation, RAG, computer vision, REST APIs, testing, monitoring, and Streamlit deployment. I care about trustworthy evaluation, explainable outputs, and software that makes a model useful.
Each project connects modeling with validation, explainability, application delivery, or operational outcomes.
Citation-grounded research over SEC 10-K/10-Q filings with section-aware processing, hybrid BM25 + FAISS retrieval, reciprocal-rank fusion, and cross-encoder reranking.
Fraud-risk pipeline with temporal data separation, probability calibration, validation-based model selection, and cost-sensitive decision thresholds.
M5 forecasting workflow using leakage-safe lag and rolling features, Seasonal Naive and LightGBM models, chronological validation, and rolling-origin backtesting.
Academic road-video screening prototype using YOLOv8 vehicle detection and tracking, custom plate-region detection, and EasyOCR transcription.
A focused toolkit for building, evaluating, explaining, and shipping data products.
Python · SQL · Pandas · NumPy · Scikit-learn · Feature Engineering · Data Analysis
LightGBM · XGBoost · Time-Series Forecasting · SHAP · RAG · BM25 · FAISS · NLP
YOLOv8 · OpenCV · EasyOCR · Object Detection · Tracking · OCR
FastAPI · REST APIs · Pydantic · Streamlit · PostgreSQL · SQLite · Docker · GitHub Actions · pytest
Matplotlib · Seaborn · Plotly · Power BI · Microsoft Excel · Jupyter
Daffodil International University
CGPA 3.33 / 4.00Let’s build something useful
I am open to entry-level roles, internships, and collaborations where careful modeling and practical engineering matter.