Waqar A.

I build machine learning systems that run in production Seven years of ML engineering, eight AI products live, and a client base that spans healthcare, fintech, e commerce, and Web3. The work covers the full lifecycle from model design, training, fine tuning, deployment, and MLOps, with a consistent delivery record of 30 to 40% measurable improvement on core business metrics. Generative AI and Large Language Models LLM fine tuning and production deployment across GPT 4, Claude, Gemini, and LLaMA. Delivered eight GenAI applications to date, including RAG systems, multi step AI agents, and enterprise chatbots built on OpenAI API, Azure OpenAI, and LangChain. Prompt engineering is treated as an engineering discipline, structured, testable, and versioned. Fluent in Hugging Face, FAISS, Pinecone, and agentic AI frameworks. Machine Learning and Deep Learning Custom model architecture using TensorFlow 2.x, PyTorch, Keras, and scikit learn. Experience spans supervised learning, unsupervised learning, transformer based architectures, BERT fine tuning, and ensemble methods built for enterprise scale, not Kaggle benchmarks. Computer Vision Real time vision systems achieving 98% plus accuracy using YOLO, ResNet, and custom CNN architectures. Deployed applications include quality control automation, medical imaging analysis, and sports performance tracking with complex occlusion handling. NLP and Conversational AI Production NLP pipelines processing 10M plus documents daily using BERT, Hugging Face Transformers, spaCy, and NLTK. Covers sentiment analysis, document classification, named entity recognition, and the full backend stack for AI chatbot development. Predictive Analytics and Time Series Forecasting models with 75 to 90% accuracy using LSTM, GRU, Prophet, and XGBoost, applied to demand forecasting, fraud detection, credit risk scoring, and customer behavior prediction. Industry Coverage Healthcare AI with HIPAA compliant clinical decision support, diagnostic algorithms, and medical imaging. Financial services including fraud detection, AML and KYC automation, algorithmic trading, and risk modeling. E commerce covering recommendation engines, dynamic pricing, and personalized AI. Manufacturing including predictive maintenance and supply chain optimization. Web3 covering on chain analytics, DeFi modeling, and wallet behavior prediction. Selected Deployments Alfred AI with 25% reduction in e commerce returns through ML powered personalization NBA Predictor with 78% match outcome accuracy, live at hyperformancepicks Valfile with NLP based talent matching and resume analysis at scale Binance Chain Analytics with 3.4TB processed and 90% recall on investor scoring InfoFinlandBot, RecorDr, Lawyerup as production GPT based systems with real users Stack TensorFlow 2.x, PyTorch, Keras, scikit learn, XGBoost, Hugging Face, LangChain, Pinecone, FAISS, OpenCV, spaCy, NLTK deployed on AWS SageMaker, Azure ML, and Google Vertex AI via Docker and Kubernetes. Python, R, SQL, JavaScript, Scala. MLflow for experiment tracking and MLOps pipeline management.