Nawaz

About Nawaz

AI Engineer | Machine Learning Developer | LLM & NLP Enthusiast | ML & AI AlumI’m a passionate Machine Learning and AI Developer with hands-on experience building intelligent systems using cutting-edge tools like LLMs, LangChain, OpenAI, and Python. I hold an Executive PG in Machine Learning & AI from Bangalore and have developed real-world AI solutions that combine domain knowledge, technical depth, and end-user value. Core Expertise: Languages & Tools: Python, LangChain, OpenAI, Hugging Face, FAISS, Scikit-learn, Streamlit AI/ML Techniques: Supervised & Unsupervised Learning, NLP, Embeddings, RAG (Retrieval-Augmented Generation), Prompt Engineering LLM Applications: Chatbots, PDF Q&A Systems, FAQ Automation, Knowledge Assistants Frameworks & APIs: OpenAI API, Hugging Face Transformers, TensorFlow (basic), REST APIs Deployment: Streamlit Apps, GitHub Projects, Lightweight AI Solutions for Business Use-Cases Projects Include:Smart FAQ Chatbot: Built with OpenAI, LangChain & FAISS for business query automationSemantic Q&A System: Domain-specific PDF chatbot using LLM + vector storeML Models: Fraud Detection, Customer Segmentation, EV Analysis, and Healthcare Predictions I love building intelligent, conversational, and autonomous AI systems that solve real-world problems. My goal is to push the boundaries of what LLMs and ML models can do for businesses, products, and users. Actively seeking AI/ML roles and open to freelance collaborations in:→ Generative AI Projects→ LLM-based Applications & Tools→ NLP & Recommendation Systems→ Custom ML Solutions & App DeploymentLet’s connect if you\'re building something smart with AI 🤖

Experience

1. Data Scientist

   Upwork

   Jan 2025 — Present

   Working as a freelance Data Scientist and ML Engineer, building AI-driven solutions across classical Machine Learning, NLP, and Generative AI. Designed Retrieval-Augmented Generation (RAG) pipelines using LangChain, embeddings, FAISS, and OpenAI API. Built early agent-style automation workflows using prompt engineering, context tuning, and reasoning chains. Developed ML models (Logistic Regression, Random Forest, XGBoost) for fraud detection, churn prediction, and forecasting use cases. Worked with Azure Databricks & PySpark for distributed data processing, ETL workflows, and feature engineering at scale. Created Streamlit-based applications for deployment, rapid experimentation, and interactive testing. Followed structured ML lifecycle practices including data ingestion, preprocessing, training, evaluation, and monitoring.Tech: Python | SQL | PySpark | Databricks | ADF | Delta Lake | LangChain | Generative AI | Streamlit | Scikit-learn | Hugging Face | OpenAI API

Education

• Osmania University

  Bachelor's degree

• Scholars Junior College

  Intermediate

• International Institute of Information Technology Bangalore

  Postgraduate Degree

• Krishnaveni Talent School

  SSC

  2007 — 2017