Hire the Best Natural Language Toolkit (NLTK) Specialists

I build production-grade agentic AI systems — multi-agent pipelines, enterprise RAG platforms, and end-to-end LLM-powered products that actually ship. My recent work includes: A 10-node LangGraph RAG platform (NexusIQ) that unifies Confluence, Slack, Jira, Google Drive, and PDFs with hybrid vector + BM25 retrieval, cross-encoder reranking, and a hallucination guard — all under 2 seconds end-to-end. An autonomous B2B SDR agent, that handles lead discovery, qualification scoring, and personalised email drafting with human-in-the-loop approval via checkpointed LangGraph state machines. A real-time Pakistan Sign Language recognition system (D-VOICE) achieving 98.25% test accuracy using a hybrid TCN+Transformer model on MediaPipe landmarks — full-stack, live inference, deployed. A fully autonomous visual novel video generator that converts a natural-language prompt into a 60 second cinematic video via 4 specialised LangGraph agents — 66/66 tests passing. What I bring to your project: → Deep LangGraph expertise: state machines, interrupts, checkpointers, multi-agent coordination → Production RAG: hybrid dense + sparse retrieval, RRF fusion, reranking, hallucination detection → Full-stack delivery: FastAPI backends, React/Next.js frontends, PostgreSQL/MongoDB, Docker → Automation & no-code: n8n, Make, and Zapier for workflow automation and API integrations — useful when you need fast turnaround without custom code → Cloud: AWS experience (EC2, S3, Lambda) for deployment and infrastructure → Clean, documented code with real test coverage not just demos I'm a CS graduate, I work like a senior engineer: I scope projects carefully, communicate proactively, and deliver systems that hold up in production not just prototypes. If you're building an AI agent, a RAG system, an LLM-powered product, or need to automate workflows with n8n/Make/Zapier — or just need someone to turn a complex idea into working software, let's talk.

Hi, I`m Noor 👋 "I turn raw data into clear, actionable insights that empower better decisions and drive real results, every step of the way." I'm a Data Scientist and AI Engineer. Over the past 5+ years, I’ve worked on projects that combine data engineering, machine learning, and large language models to build intelligent, production-ready solutions. I specialize in designing end-to-end ML pipelines, developing LLM-powered applications (RAG, LangChain, Llama-2/3, OpenAI), and deploying scalable systems on Azure, Databricks, and Docker. My work often involves automating data workflows, improving prediction accuracy, and transforming complex data into clear insights. Some of my favorite projects include building an AI chatbot for e-commerce, a predictive system for event planning, and an IoT protocol translator using LLMs. I value clarity, efficiency, and collaboration and I always aim to deliver results that make a measurable impact. If you’re looking for someone who can turn your data or AI idea into a working solution, I’d be happy to help.

🥇 AI Engineer & Data Scientist | 1+ Year Experience I’m an AI Engineer and Data Scientist passionate about building intelligent, automated, and data-driven systems that solve real-world problems. With expertise in Machine Learning, Generative AI, NLP, Computer Vision, and workflow automation, I help startups and enterprises create AI solutions that scale and deliver measurable impact. What I Can Deliver ➤ AI Agents & Chatbots • RAG-based multi-PDF and document Q&A systems using LangChain, FAISS, HuggingFace, and Gemini AI • Custom AI agents and chatbots powered by OpenAI, GPT, Claude, and Mistral • Voice and calling agents with Retell AI and real-time API integrations • CRM & email automation integrated with Slack, Gmail, and HubSpot ➤ Computer Vision & Image Analysis • Deep learning-based image classification, object detection, and feature extraction • Convolutional Neural Networks (CNNs), transfer learning, and data augmentation for high-accuracy predictions • Real-time image processing deployed with Flask/Django apps • Projects include pet image classification, facial attribute detection, and AI-based image analytics ➤ Workflow Automation & Orchestration • Intelligent automation pipelines using Python, n8n, Make.com, and Zapier • Lead management, reporting, and data syncing workflows • API, database, and CRM integrations to automate repetitive tasks ➤ Machine Learning & Data Science • NLP, deep learning, predictive modeling, and feature engineering • LLM fine-tuning (BERT, GPT, HuggingFace Transformers) • Recommendation systems, forecasting, and regression models • Model deployment with Flask, FastAPI, Django, and Docker ➤ Data Engineering & Business Intelligence • ETL processes, SQL pipelines, and cloud integration (Azure) • Real-time dashboards and analytics using Power BI & Tableau • Data-driven reporting and KPI tracking Technical Skills Python, Flask, Django, JavaScript, HTML, CSS, OOP NumPy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace, FAISS, OpenAI API, NLP, RAG, Computer Vision n8n, Make.com, Zapier, Retell AI, API Integrations, Workflow Automation SQL, ETL, REST APIs, Web Scraping, Azure, Docker Git, GitHub, Jupyter Notebook, Google Colab, VS Code I specialize in building AI systems that automate processes, analyze visual and textual data, deliver actionable insights, and enhance business efficiency. 📍 Available for short-term & long-term projects | NDA-Compliant | Reliable & Collaborative

I build and ship production AI systems that real users depend on, not demos. RAG pipelines, multi-agent LLM apps, fine-tuned models, and multimodal/OCR extraction, deployed to run 24/7 on Kubernetes and serverless GPU. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Top-Rated Plus | 100% Job Success | 4+ years ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Enterprise-grade AI for multinational companies and startups, including HIPAA-conscious healthcare workflows. I turn complex requirements into intelligent, production-ready applications that drive measurable results. ━━━━━━━━━━━━━━━━━━━━━ WHAT I DO BEST ━━━━━━━━━━━━━━━━━━━━━ Agentic AI & Multi-Agent Systems Custom architectures with LangGraph, CrewAI, and Model Context Protocol (MCP), including self-improving agents that learn from evaluation feedback. Built for real automation, not chatbot demos. Advanced RAG, Evaluation & Observability 10+ production RAG systems (self-RAG, adaptive retrieval), one serving hundreds of users across thousands of documents. Migrated Pinecone to Weaviate for better recall at lower cost. Every system ships with LLM-as-judge, retrieval metrics, and full tracing (LangSmith/Langfuse), so quality is measured, not guessed. LLM Fine-Tuning & Cost Optimization PEFT (LoRA/QLoRA), SFT, DPO, and instruction tuning. Fine-tuned a 7B Arabic model served on autoscaling serverless GPU, plus multimodal vision-language models. Cut client AI costs by up to 40% through open-source replacement and quantization, with no drop in performance. Multimodal & Document AI OCR and document-extraction pipelines across PDF, DOCX, PPTX, Excel, and images, with strong F1 on messy financial and clinical documents. Also built a temporal, multi-hop knowledge graph over an encrypted Postgres + Qdrant store with client-side encryption. AI Automation & Integrations Connecting LLMs to real business systems: n8n, Make (Integromat), Zapier, CRM automation (HubSpot, GoHighLevel, Airtable), Supabase backends, and Twilio/WhatsApp. AI that plugs into how your team actually works. Enterprise Backend & Scalable Infra Master-level Python (FastAPI, Flask), robust CI/CD, and multi-cloud deployment (AWS, Azure, GCP). Docker + Kubernetes with KEDA autoscaling, plus privacy-first, multi-tenant systems (E2EE, RBAC, audit logging), including HIPAA-conscious PHI handling. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TECH STACK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ Agents & LLMs: LangChain, LlamaIndex, LangGraph, CrewAI, MCP, Hugging Face (PEFT/TRL), Ollama, TGI, vLLM ▸ Eval & Tracing: LangSmith, Langfuse, LLM-as-judge, custom eval frameworks ▸ Vector DBs: Weaviate, Pinecone, Qdrant, FAISS, ChromaDB ▸ Models: OpenAI, Claude, Gemini, fine-tuned open-source ▸ Automation: n8n, Make (Integromat), Zapier, Supabase, Twilio ▸ Backend: Python (FastAPI, Flask), TypeScript/Node (NestJS, NextJS), PostgreSQL, MongoDB ▸ MLOps & Cloud: Docker, Kubernetes, KEDA, CI/CD, Airflow, MLflow; AWS (SageMaker, Lambda), Azure ML / Azure OpenAI, GCP, serverless GPU ▸ CV & Data: OCR optimization, vision-language models, Stable Diffusion, web scraping ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY CLIENTS PICK ME ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ Ships to production. I build AND deploy. You get systems that run 24/7 and scale, not a prototype someone else has to finish. ▸ Proven track record. Top-Rated Plus, 100% Job Success, enterprise and healthcare AI delivered end-to-end. ▸ Innovation-driven. I bring the latest (MCP, adaptive RAG, new model releases) into production. ▸ Cost-conscious. High-performance AI that optimizes spend without compromising quality. ▸ Quality-first. Production-grade code, proper testing, and evaluation built in. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Building an AI product, or need one taken from prototype to production and scaled reliably? Send me the brief and I'll tell you exactly how I'd approach it.

I design and deploy AI systems that don’t just launch, they scale and perform reliably in production. With 50+ live deployments and 100% client satisfaction, I’ve built everything from intelligent AI solutions and Chatbot Development projects to advanced Computer Vision pipelines and predictive Machine Learning models. As an AWS Certified AI Engineer and Head of AI, I specialize in end-to-end AI architecture using Python, PyTorch, TensorFlow and modern cloud platforms like Amazon Web Services, Azure and DigitalOcean. My expertise spans AI Agent Development, Natural Language Processing, Retrieval Augmented Generation, Deep Learning, Data Science and advanced Data Analysis, delivering robust MVPs and fully production-ready AI platforms that drive real business impact. Notable Achievements: ✦ Reaktion: Developed an AI-powered chatbot using Machine Learning and NLP to deliver advanced Data Analytics and dynamic Data Visualization directly from database queries. Reduced manual reporting effort by 60%. ✦ Partfiniti: Automated BOM extraction from PDFs, emails, excel and images into structured JSON with part lookup and natural language generation, improved extraction accuracy to 92%. ✦ Finsight: FinTech forecasting platform on AWS (EC2, RDS, S3) with FastAPI, Streamlit and predictive ML models, improved forecasting accuracy by 28%. ✦ GIS Mineral Analytics: Built end-to-end ETL pipelines with PostGIS, kriging, KNN, IDW and anomaly detection to power predictive mineral mapping and dynamic heatmaps, reducing exploration risk by 28% and improving drill targeting accuracy by 35%. Areas of Expertise: ✦ Machine Learning: (scikit-learn, XGBoost, Time-Series Forecasting), Python (FastAPI, Streamlit) ✦ Gen AI: LLMs, NLP, RAG Pipelines, OpenAI, Llama, AI Agents, ChatGPT ✦ Audio and Speech AI: AI Voice Agents, STT, TTS, TensorFlow Audio Classification APIs ✦ Computer Vision: OCR, Object Detection, Segmentation, Emotion Detection, Image Recognition (OpenCV, Tesseract), Image Generation, Data Extraction ✦ Cloud-Native AI: AWS Lambda, EC2, RDS, S3, Azure AI, FastAPI, Streamlit, API integration, secure backend systems Why do clients love working with me? ✦ Successfully launched production-ready AI/ML systems with measurable business impact. ✦ Scalable, high-quality solutions powered by Generative AI and Machine Learning. ✦ Reliable long-term partner focused on clarity, performance and sustainable growth. ✦ Strong balance of deep technical expertise and real-world business outcomes across multiple industries. 💬 Feel free to reach out anytime! Let’s build the AI-powered success your business deserves and transform your ideas into production-ready impact!

I build production-grade GenAI systems for Fortune 500 enterprises including Verizon and PNC, : AI agents, RAG platforms, semantic layers, knowledge graphs, text-to-SQL/NLQ systems, and full-stack AI applications. I have 9+ years of experience across machine learning, computer vision, NLP, backend engineering, and full-stack product development. Recently, I have led large engineering teams building enterprise AI platforms for telecom and banking use cases. What I can help you build: • AI agent systems using LangGraph, LangChain, MCP, A2A, FastAPI, and custom tool orchestration • RAG applications over documents, databases, knowledge bases, and enterprise data • Semantic layers and ontology-driven systems for analytics and GenAI use cases • Text-to-SQL / natural language database querying over Postgres, BigQuery, and Teradata • Knowledge graph RAG using Neo4j, vector databases, metadata extraction, and domain modeling • Full-stack AI SaaS products with Python, React, Next.js, Docker, Kubernetes, and cloud deployment • LLM fine-tuning, evaluation, prompt engineering, retrieval evaluation, and hallucination reduction Relevant achievements: • Led a 14-member team to build an asynchronous, extensible, A2A-compliant agentic framework for enterprise troubleshooting. • Reduced ticket resolution time in a production troubleshooting workflow from days to minutes. • Built and deployed hundreds of tools across multiple MCP servers. • Led a 12-member team to build a natural language query platform for enterprise databases. • Improved NLQ accuracy using domain modeling, metadata generation, and knowledge graph traversal. • Built an ontology-powered Knowledge Graph RAG platform over unstructured enterprise data. • Co-founded and scaled an AI video translation/dubbing product from $0 to $100k revenue in 6 months. • Built computer vision systems deployed across industrial locations in India and Europe. Tech stack: Python, FastAPI, LangChain, LangGraph, LlamaIndex, OpenAI, HuggingFace, PyTorch, PEFT/LoRA, React, Next.js, Postgres, BigQuery, Neo4j, Pinecone, Docker, Kubernetes, ArgoCD, GCP, AWS, PySpark, Airflow. I am best suited for clients who need more than a prototype. I can help you go from ambiguous AI idea → system design → implementation → deployment → evaluation → production hardening.