Nada S.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

5+ years building production machine learning systems. IEEE-published researcher in applied ML. Top 10% on Upwork, 100% Job Success. I build ML and AI systems that go from raw data to production, not demos, not notebooks, systems that run under real users, real data volume, and real deadlines. My work spans predictive modeling, NLP, computer vision, and LLM-powered applications. Recent projects include a SageMaker pipeline processing 109M+ rows for a client's core ML workflow, and production LLM/RAG systems built on LangChain and Hugging Face for document analysis and workflow automation. My published research shapes how I approach model selection: I default to the simplest architecture that clears the bar, and I can defend every modeling decision I make. Where I operate: Modeling - forecasting, classification, and regression on production-scale data; NLP (NER, summarization, classification); computer vision (YOLO, OpenCV) when the problem genuinely calls for it. LLM/RAG systems - retrieval architecture, evaluation harnesses, and cost-aware model routing (OpenAI, vLLM, Hugging Face), built to be monitored and debuggable — not a black box your team inherits and fears touching. Data engineering - ETL and feature pipelines past 100GB, with reproducibility (MLflow, Airflow) treated as a requirement, not a nice-to-have. Deployment - I own the full path from model to production: FastAPI/Flask services, Docker, CI/CD, AWS infrastructure. What I hand off is something your engineers can operate without me. Clients across the US and internationally. I scope honestly before I start, if a project needs more data, more time, or a different approach than what's been asked for, I say so before you've spent a dollar, not after.