Tayyab T.

Senior AI/ML engineer building machine learning, NLP, LLM, RAG, and AI agent systems, plus Voice AI and n8n automation workflows. 𝐒𝐭𝐚𝐧𝐟𝐨𝐫𝐝 𝐌𝐒 𝐢𝐧 𝐀𝐈, 𝐄𝐱𝐩𝐞𝐫𝐭-𝐕𝐞𝐭𝐭𝐞𝐝, 𝐓𝐨𝐩 𝐑𝐚𝐭𝐞𝐝 𝐏𝐥𝐮𝐬, 100% 𝐉𝐨𝐛 𝐒𝐮𝐜𝐜𝐞𝐬𝐬. I've worked on machine learning and NLP projects on Upwork since 2015, mostly for healthcare, legal, finance, and insurance teams. Clients usually come to me with a prototype that broke on real data, a half-built product that needs finishing, or a manual process they want automated. I lead architecture and technical discovery, and senior engineers at Red Buffer build alongside me from requirements through deployment and monitoring. 𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃 𝐌𝐀𝐂𝐇𝐈𝐍𝐄 𝐋𝐄𝐀𝐑𝐍𝐈𝐍𝐆 & 𝐃𝐀𝐓𝐀 𝐒𝐂𝐈𝐄𝐍𝐂𝐄: Prediction, classification, forecasting, anomaly detection, NLP, and computer vision (object detection, OCR) on real business data. 𝐋𝐋𝐌 𝐀𝐏𝐏𝐒, 𝐑𝐀𝐆 & 𝐀𝐈 𝐀𝐆𝐄𝐍𝐓𝐒: Assistants and search over your own documents, with citations back to the source. Agents that call your tools and APIs, run multi-step workflows, and hand off to a person when they're unsure. 𝐃𝐎𝐂𝐔𝐌𝐄𝐍𝐓 𝐀𝐈: Extraction and analysis for contracts, medical records, invoices, and financial documents, with checks that flag low-confidence results before they reach a user. 𝐀𝐈 𝐀𝐔𝐓𝐎𝐌𝐀𝐓𝐈𝐎𝐍: AI connected to your CRM, databases, email, chat, and internal tools: customer support, sales workflows, reporting, and back-office tasks, built with n8n and Python. 𝐕𝐎𝐈𝐂𝐄 𝐀𝐈: Voice assistants for call handling, clinical intake, and customer support. 𝐅𝐔𝐋𝐋-𝐒𝐓𝐀𝐂𝐊 𝐀𝐈 & 𝐌𝐕𝐏𝐬: End-to-end AI products and SaaS, from first build to production, including taking over and finishing stalled projects. MLOps to turn models into production APIs. 𝐒𝐓𝐀𝐂𝐊 Models: OpenAI, Claude, Gemini, Llama, Azure OpenAI Service Agents: LangGraph, OpenAI Agents SDK, CrewAI, MCP Backend: Python, FastAPI, Node.js, React, Next.js, PostgreSQL, Supabase ML & vision: TensorFlow, Detectron2, Tesseract OCR Cloud: AWS (Solutions Architect Associate), Azure, GCP, Docker, n8n 𝐒𝐄𝐋𝐄𝐂𝐓𝐄𝐃 𝐑𝐄𝐒𝐔𝐋𝐓𝐒 - Cut contract review time by 60-70% with NLP clause extraction and human review - Predicted insurance claim costs at 90% accuracy from medical records - Processed 600-page medical PDFs in under five minutes - Removed 90% of manual data entry in invoice and purchase-order processing - Cut ML model deployment from days to minutes with automated MLOps - Built the AI/ML core of a cloud cost platform that cut spend 25% 𝐇𝐎𝐖 𝐈 𝐖𝐎𝐑𝐊 I agree on the architecture with you before any code is written, and I set up testing so you can see how accurate the system is. I plan for failures with retries, logging, and human review. This matters most in healthcare, legal, finance, and insurance, where wrong answers cost money. 𝐆𝐎𝐎𝐃 𝐅𝐈𝐓 𝐈𝐅 - You need an AI or ML product built, or a half-built one taken over and finished - You want operations automated with AI, connected to your CRM, email, and business tools - You need Voice AI, document AI, or computer vision - You need a data scientist for forecasting, NLP, or predictive modeling - You want an architecture review before committing budget Invite me to your job post, or send a short description of what you're building and where it's stuck. I'll tell you honestly whether it's a good fit and what I'd do first. Keywords: Artificial Intelligence, Deep Learning, NLP, Generative AI, LLM, ChatGPT, OpenAI, Claude, Gemini, Llama, RAG, AI Agent, Agentic AI, Multi-Agent Systems, MCP, LangGraph, Function Calling, Voice AI, Conversational AI, Chatbot, Prompt Engineering, Document AI, Data Extraction, OCR, Computer Vision, TensorFlow, AI Automation, Workflow Automation, n8n, MLOps, Python, FastAPI, Node.js, React, Next.js, PostgreSQL, Supabase, Docker, AWS, Azure, GCP, Full-Stack Development, Healthcare AI