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I am a research engineer focusing upon building and surpassing the latest and greatest in AI. My focus is on natural language processing (NLP) and multimodal (vision and text) AI, with a particular emphasis on large generative models. I have extensive experience working with a variety of different clients, from new startups backed by Y Combinator and AllenAI to large Fortune 500 companies. I have also provided consulting services, including to various venture capital firms and former Microsoft, AWS, and RTL Group executives hoping to build their own AI businesses. I am certified as a top 1% expert on Upwork and within the top 10% by Triplebyte. I also give talks across the industry - for example, I recently spoke on the Weaviate podcast about the current multimodal AI landscape. In terms of the models I am experienced with, I have worked with the vast majority of NLP and multimodal models as well as a significant amount of the speech and vision models available on Huggingface. I regularly build my custom model architectures to best fit client needs since while most models only really have one advancement they focus on, the clients I work with usually would benefit from the improvements from several different Huggingface models. However, I am also familiar with proprietary AI APIs, particularly that of OpenAI’s. I usually recommend those to clients who either will not see a lot of usage of their AI products for a while or those who have low maintenance costs being a top priority. Some of my favorite projects include: - Building a video summarizer taking as input a video or audio file and outputting a summary of its contents in either text or audio format. I used my own custom punctuation addition model, chunking and batching of speech inputs into 10 second increments to speed up transcription, TGlobal attention for the summarization system, and many other tricks. - Building a ChatGPT-style question answering chatbot built entirely with open-source models and tools - Creating a medical bill reimbursement system that took as input a picture of a medical bill, extracted the names of any relevant medical treatments, compared them using semantic search to reimbursable medical procedures in an insurer’s database, and automatically paid out money for all matches - Adding fine-tuning capabilities to MiniGPT-4 and other multimodal LLMs - Domain adapting CLIP on e-commerce data, reaching a 57% relative improvement in zero-shot classification after just 1 hour of training - Creating a custom training framework to train encoder-based language models using the replaced token detection (RTD) objective, including supporting weight sharing, custom generator sizes, training on multilingual datasets, adaptation of models not originally trained with RTD to be trainable using the task, etc. - Building a custom multimodal model architecture using linear attention - Reducing the size of the intent classification and NER models of an automotive company’s Alexa-style virtual assistant by 95-99% while improving accuracy - Creating the state-of-the-art ASL to English translation system back in 2021 (though I surmise this has since been dramatically improved upon since) Tech Stack: Model Development and Optimization - Huggingface, PyTorch, ONNX, Datasets, Pandas, Numpy, Scipy, SciKit-Learn, Sentence Transformers, PEFT, Accelerate, Loralib, TensorRT, Fairseq, LAVIS, TIMM, OpenNMT, TensorFlow, Jax, lots and lots of others Visualization - Matplotlib, tSNE, UMAP LLM Tools - OpenAI API (GPT-4, 3.5 turbo, Ada through davinci, etc.), Langchain, LLaMaIndex, Weaviate, Pinecone, Faiss, ScaNN Cloud - AWS (Sagemaker, EC2), GCP, Azure. I prefer to avoid cloud companies’ end to end AI services (e.g., Amazon Comprehend) since they tend to be inferior to open-source alternatives or things I can custom build, though I am open to using them if that is what you prefer!

Having over 10 years of experince, I lead the architecture and delivery of enterprise AI solutions that transform complex business processes through intelligent automation, predictive analytics, and production-grade machine learning systems. Prior to this, I served as a Senior AI/ML Consultant at CVS Health and as a Principal Data Scientist at Walgreens, where I worked on large-scale healthcare AI initiatives supporting Fortune 500 organizations. These experiences have shaped my approach to engineering AI systems that prioritize scalability, maintainability, security, and measurable business outcomes rather than experimental proofs of concept. My expertise spans the complete machine learning lifecycle. From data engineering, feature engineering, statistical modeling, and predictive analytics to MLOps, model deployment, monitoring, and continuous optimization, I build end-to-end AI platforms that deliver value long after deployment. I have extensive experience developing LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, conversational AI, intelligent document processing pipelines, recommendation systems, forecasting models, and production APIs capable of serving AI workloads at scale. On the engineering side, I work extensively with Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM, FastAPI, Docker, Kubernetes, MLflow, PostgreSQL, Apache Spark, Snowflake, Databricks, and modern cloud platforms including AWS, Google Cloud Platform, and Azure. I also build advanced Generative AI solutions using OpenAI, Claude, Gemini, Llama, LangChain, LangGraph, LlamaIndex, and multi-agent architectures to solve complex business challenges through intelligent automation and decision support. What differentiates my work is a production-first mindset. I don't simply develop machine learning models, I engineer complete AI ecosystems. That means designing scalable data pipelines, deploying resilient model-serving infrastructure, implementing monitoring and CI/CD workflows, integrating AI seamlessly into existing software stacks, and ensuring every solution is maintainable, observable, and built for long-term growth. Whether you're looking to build a production-ready machine learning platform, operationalize existing models through modern MLOps practices, develop enterprise-grade LLM applications, or create intelligent data products powered by advanced analytics, I bring the technical depth and enterprise experience to deliver solutions that are both innovative and dependable. If you're looking for an engineer who understands both the science behind machine learning and the engineering required to deploy it successfully at scale, I'd be happy to discuss how we can build your next AI solution.

With a Ph.D. in Interdisciplinary Linguistics, M.A. in English, and 20+ years of experience as a professor, writer, editor, and researcher, I offer professional skills and knowledge in editing, writing, teaching, and consultation regarding linguistics, literature, English grammar, semantics, and computational linguistics. I have taught university courses in all of these subject areas for years, most recently, and mostly, at Tulane University. I am also interested and educated in cognitive science, philosophy of the mind, and self-development. I am a certified tai chi / qi gong instructor and I have written dozens of articles about meditation, neurofeedback, hypnosis, and other related topics. My "interdisciplinary" Ph.D. is interdisciplinary between cognitive, anthropological, and philosophical linguistics. For the last few years I have worked most in computational linguistics, natural language processing, and AI-training by RLHF.

I am a Top-Rated Python Developer with 8+ years of hands-on expertise delivering high-impact solutions across Machine Learning, Automation, NLP, LLM, AI Agent, Web Scraping, and Full-Stack Applications. I specialize in building robust, scalable, production-ready systems that transform raw data into actionable insights and operational success. 🔹 Core Technical Expertise: • Machine Learning & Predictive Analytics: Expert in developing end-to-end predictive maintenance systems, handling feature engineering, EDA, anomaly detection, model building (Decision Trees, Random Forests, XGBoost, Gradient Boosting, k-NN), model evaluation, and deployment using Pickle and Gradio. • NLP & Semantic Search Applications: Built full-stack Streamlit apps with Sentence-Transformer embeddings, integrating semantic search engines with custom cosine similarity scoring and SQLite storage, enabling intelligent content retrieval. • LLM & AI Agent: Built RAG chatbot using LLM with Langchain and Langsmith that specifically designed for customer requirements and handled API orchestration with real time notification service by scheduling and clone job using AI Agent. • Automation & Email Campaign Systems: Engineered secure, personalized email automation pipelines using smtplib, MIME libraries, and pandas, capable of mass email dispatch with live tracking, randomized sending, and user-specific content customization. • Web Scraping & Data Extraction: Developed multi-threaded web crawlers using Requests, BeautifulSoup, Regex, and ThreadPoolExecutor, capable of extracting structured data (e.g., emails) at scale with robust error handling and compliance with ethical scraping practices. • Data Cleansing & Entity Matching: Automated fuzzy matching pipelines leveraging FuzzyWuzzy and Levenshtein Distance to intelligently reconcile messy datasets, achieving high match rates across multi-format Excel datasets. • ETL Pipelines & Data Engineering: Built scalable ETL workflows for ingestion, normalization, and validation of structured and unstructured data from APIs, databases, and file systems using pandas, NumPy, Azure Data Factory, and Alteryx. • Visualization & Reporting: Produced powerful interactive visualizations and dashboards using Matplotlib, Seaborn, Plotly, and Power BI, enabling data-driven decision making for business and technical stakeholders. • Deployment & Optimization: Expert in caching optimization using Streamlit caching, model serialization with Pickle, scalable database storage using SQLite, and efficient deployment pipelines for Python-based web apps and data services. 🌍 Industries Served: Healthcare (Patient Monitoring, Predictive Risk Analysis) Manufacturing (Predictive Maintenance, Anomaly Detection) Retail (Sales Forecasting, Data Cleaning) Technology Startups (NLP Search Systems, Web Automation) Marketing Agencies (Lead Generation, Email Automation) Research & Education (Data Mining, Interactive ML Apps) ✅ What I Deliver: • 🛠️ Clean, production-ready, and scalable Python code • 💡 Business-aligned machine learning and automation solutions • 📈 Insightful, actionable visualizations and reporting dashboards • 🔄 Agile collaboration with flexible time zone availability • 🔒 Data security, compliance (HIPAA, GDPR), and ethical practices • 📩 End-to-end deployment including APIs, dashboards, or deliverables • 🌟 100% client satisfaction and long-term support 🚀 Ready to Transform Your Data or Automate Your Workflow? Whether you need a smart predictive model, a scraping bot, an automation system, or an intelligent search engine, I'm here to build high-quality, customized solutions that drive results. 📩 Let’s connect and turn your ideas into impactful Python solutions!

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.

🤖𝐈𝐟 𝐦𝐲 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐝𝐨𝐞𝐬𝐧’𝐭 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐲𝐨𝐮𝐫 𝐚𝐠𝐫𝐞𝐞𝐝 𝐦𝐞𝐭𝐫𝐢𝐜𝐬, 𝐲𝐨𝐮 𝐝𝐞𝐬𝐞𝐫𝐯𝐞 𝟏𝟎𝟎% 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐦𝐨𝐧𝐞𝐲 𝐛𝐚𝐜𝐤. Most businesses hire AI developers to build what they ask for. That's the problem. I don't just build what clients request - I figure out what they actually need first. Usually what they think they need isn't the highest-ROI opportunity. AI-powered solutions delivering production-ready systems measurable ROI and high-impact results - not just prototypes. Work spans finance, healthcare, e-commerce, construction, academia and web platforms, often unlocking $100K–$300K in annual savings 𝐍𝐄𝐗𝐓 𝐒𝐓𝐄𝐏𝐒:- Send me a message with your project problem, budget & timeline. I’ll reply within 24 hours to confirm if I’m the right fit. What Is Built / How Problems Are Solved with AI: ▶️ Multi-Agent AI Systems (LangGraph, LangChain) ▶️ Custom RAG Pipelines (OpenSearch, Pinecone, Supabase) ▶️ Voice AI (VAPI, ElevenLabs, LiveKit) ▶️ Sales & Support Automation (chat + voice) ▶️ Process Automation (n8n, Make, Zapier) ▶️ Full-Stack Development (Node.js, Python, React, Next.js, React Native) ▶️ Dashboards, forecasting models, ETL pipelines ▶️ Chatbots for WhatsApp, Telegram, SMS (via Twilio) My Portfolio Includes: ✔️ Generative AI development: GPT-4o, Claude, Mistral, Llama, Hugging Face, LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, Qdrant, Stable Diffusion, Flux 1.1, Ideogram, Lora, n8n, Agentic AI, CrewAI, BabyAGI, AutGen, DeepSeek, Prompt Engineering ✔️ Cost & performance optimization of AI applications ✔️ Time series forecasting models ✔️ ETL & data automation (Airtable, Webflow, Make) ✔️ AI Web development (Django, Flask, Dash with ML models) ✔️ Payment Gateway Integration ✔️ Dashboard development (Plotly Dash, PowerBI, Excel, Looker) ✔️ Data Analytics & Reporting ✔️ Translating business problems to technical teams ✔️ Geospatial Mapping ✔️ Chatbot integration (WhatsApp, Telegram, SMS via Twilio) ✔️ API development & integration ✔️ Research Publications Tech Stack/ Expertise: ⏺️ Python Libraries: Scikit Learn, Pandas, Numpy, Plotly, Tensorflow, Facebook Prophet, Spacy, NLTK, GeoPandas, OpenAi, LangChain, HuggingFace, Matplotlib, Seaborn ⏺️ Web Development: Dash, Django, Flask, FastAPI, Docker, MySQL, MS SQL, Pinecone, HTML5, CSS3, JavaScript ⏺️ MS Office: Excel (Advanced), PowerPoint (Advanced), Word (Advanced), Project ⏺️ Data Visualization / BI: Power BI, Looker, Tableau ⏺️ Front-end Tools: HTML5, CSS3, JavaScript ⏺️ Big Data Tools: PySpark, Hadoop ⏺️ Web-Scraping: Beautiful Soup, Scrapy, Selenium, Playwright ⏺️ Version Control: Git ⏺️ ERP Tools: SAP, Hysabat ⏺️ Cloud Technology: GCP, AWS, Azure, Digital Ocean Why Clients Hire: ⭐ Guidance on what NOT to build (most consultants won’t do this) ⭐ 5.0 rating ⭐ Production systems with metrics, logs, and clean handoffs ⭐ Coordinate senior engineers across ML, data, and cloud ⭐ Clear communication and global availability Let’s build AI solutions that actually work. #AIAgentDevelopment #DataAnalysis #DataEngineering #CloudComputing #PredictiveModeling #MLOps #ImageProcessing #AIChatbot #Python #OpenAIAPI #VectorDatabase #ArtificialIntelligence #RAG #LangChain #Pinecone #MultimodalAI #ProductionDeployment #Deep Learning #Artificial Neural Network #Chatbot Development #Computer Vision #Natural Language Processing #Machine Learning #Artificial Intelligence Ethics #Artificial Intelligence #Chatbot #Machine Learning #Deep Neural Network #Data Visualization #Data Analysis #Information Analysis #Data Science #Data Cleaning #Prompt Engineering #Generative AI #Large Language Model #Granite