Senior Computer Vision Engineer specializing in production-ready AI systems. Over the past 5+ years, I have designed, trained, optimized, and deployed computer vision solutions across medical imaging, biotechnology, agriculture, remote sensing, and industrial applications. ✦ Core Specializations ─────────────────────────────────────────── ⚡ Object Detection & Real-Time Inference Custom detection pipelines built on YOLO, RT-DETR, RF-DETR & Detectron2. Single-modal and multi-modal. Optimized for speed, accuracy, and edge deployment — not just benchmark scores. ⚡ Medical & Biotech Image Analysis Classification, segmentation & prediction systems for clinical and research environments. Calibrated outputs, ordinal grading, custom loss functions designed for domain-specific constraints where off-the-shelf fails. ⚡ Multispectral & Aerial Computer Vision RGB, NIR, thermal — cross-modal fusion architectures for remote sensing, livestock monitoring & precision agriculture. Full pipeline ownership from raw sensor calibration to production-ready detection. ⚡ Video Intelligence & Motion Analysis Action recognition, temporal modeling & tracking from video. Real-time inference pipelines containerized and deployed on cloud GPU infrastructure. ✦ Technical Stack ─────────────────────────────────────────── Computer Vision: PyTorch · OpenCV · YOLO · RT-DETR · RF-DETR · Detectron2 · DINOv2 · Vision Transformers · SAM Image Processing: Camera Calibration · ChArUco · ArUco · Chessboard Calibration · Fisheye Calibration · Stereo Calibration · Image Undistortion · Image Rectification · Geometric Vision Machine Learning: Deep Learning · Classification · Segmentation · Tracking · Action Recognition · Pose Estimation · Multi-Modal Learning Deployment & MLOps: FastAPI · Docker · AWS · GCP · ONNX · TensorRT · CI/CD ✦ What to Expect ─────────────────────────────────────────── Requirements Discovery → Solution Design → Structured Milestones → Weekly Demos & Progress Updates → Production-Grade Delivery → Post-Deployment Support → Send a message with project details to get started.

I build AI systems that hold up in production. LLM agents, multi-agent pipelines, RAG architectures, and the automation around them, engineered with the safety boundaries and test coverage that keep them reliable once real users depend on them. I am an AI engineer with an Bachlor in Generative AI from the University of Texas at Dallas and a prior background in production software and contact-center systems integration. Over the past year I shipped work across more than 30 repositories, spanning AI agents, RAG systems, and full-stack AI products, including open-source tools published to npm. My work is grounded in real engineering discipline: spec-first design, test-first implementation, and containerized deployment with CI/CD. What sets my AI work apart is that I treat the model as one component in a system, not the whole system. The LLM proposes, deterministic code decides. That is how I build agents that can take real action without acting dangerously. 💡 What I build ⬡ AI agents and multi-agent systems with CrewAI, AutoGen, LangGraph, and LangChain that coordinate real tasks end to end ⬡ RAG pipelines with LlamaIndex, FAISS, pgvector, and sentence embeddings that ground LLMs in your own knowledge base ⬡ LLM-in-the-loop systems with hard safety boundaries, where a deterministic rule engine authorizes every action the model proposes ⬡ MCP servers that expose your tools to Claude and other agents natively over JSON-RPC ⬡ Workflow automation with n8n, Zapier, and Playwright browser automation that runs unattended with real error handling and retries ⬡ Production APIs in FastAPI, Django, and Flask, and full-stack apps in React 19 and Next.js ⬡ Provider-agnostic LLM integration across OpenAI, Anthropic, Google, Groq, Mistral, and local Ollama models behind one interface 🛠️ Selected work orch, an open-source CLI published to npm that routes prompts across multiple AI coding agents through a single interface, with budget-aware selection learned from real quota and rate-limit failures A human-in-the-loop review service for AI-authored documents: a containerized HTTP API plus an MCP server exposing 20 review tools, deployed multi-user behind OAuth An LLM trading research bot on the Binance test network, where the model reasons over market data through read-only tools and a deterministic risk engine is the only path to an order, verified live and backed by roughly 470 tests A full job-application platform: a FastAPI agent service that scouts, scores, and tailors applications across six sources, with a provider-agnostic LLM layer and Playwright auto-apply, fronted by a Next.js dashboard An autonomous server-maintenance agent packaged in Docker, and a Chrome extension that fills web forms from your own documents using a pluggable local-or-cloud AI layer 🧠 Background and research Generative AI, University Texas at Dallas. My dissertation studies whether large language models actually know what they do not know, probing model calibration and hallucination at knowledge boundaries. I also write about LLM reliability on my engineering blog. Before that I spent years in production software and contact-center systems integration with tools like Cisco Finesse, ActiveMQ, and Jira automation, so I am comfortable both building greenfield AI products and working inside existing enterprise systems. 🛠️ Core stack Languages: Python, TypeScript, Go, JavaScript AI: LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, MCP, OpenAI API, Anthropic API, Gemini, Groq, Ollama, RAG, PyTorch, Hugging Face Backend: FastAPI, Django, Flask, NestJS, Node.js Frontend: React 19, Next.js, TypeScript, Tailwind Data: PostgreSQL, SQLite, FAISS, pgvector, Redis, Firebase Infrastructure: Docker, Docker Compose, GitHub Actions, CI/CD, Nginx, VPS deployment If you need an LLM agent, a multi-agent system, a RAG pipeline, or a full-stack AI product built by someone who cares whether it still works next month, send me a message and tell me what you are building. I will tell you honestly whether I am the right fit. Keywords: AI Engineer, LLM Developer, AI Agent Development, Multi-Agent Systems, RAG Systems, LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, MCP, Model Context Protocol, OpenAI API, Anthropic Claude, Python Developer, FastAPI, Django, Next.js, React, TypeScript, LLM Integration, Prompt Engineering, Vector Databases, Workflow Automation, Playwright, Generative AI, Machine Learning, Ollama, AI Automation

🔵 AI Automation & NLP Solutions Expert 🔵 Trusted by global clients for real-world AI systems 🔵 Builder of intelligent chatbots, LLM tools & business automation 🔵 Delivering fast, scalable, production-ready AI solutions Most businesses don’t struggle with ideas. They struggle with manual work, slow processes, and inefficient systems that waste time, money, and opportunity. 𝗡𝗼𝘄 𝗶𝗺𝗮𝗴𝗶𝗻𝗲 𝘁𝗵𝗶𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱: 🔵 Customer support handled by an intelligent AI chatbot 🔵 Repetitive workflows fully automated 🔵 Data turned into clear, actionable insights 🔵 Business running faster, smarter, and more efficiently Without large teams. Without complex infrastructure. Without wasted effort. That’s the transformation I build. 𝗪𝗵𝗼 𝗜 𝗔𝗺 I’m an AI Developer, NLP Engineer, and Automation Specialist focused on turning complex ideas into real, working AI solutions that deliver measurable business impact. 𝗥𝗲𝗰𝗲𝗻𝘁𝗹𝘆 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 𝗮𝗻 𝗡𝗟𝗣 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 & 𝗺𝗼𝗱𝗲𝗹 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝘄𝗶𝘁𝗵: 🔵 5⭐ client feedback 🔵 Faster processing performance 🔵 Clean production-ready deployment 🔵 Reliable real-world usability Because success isn’t writing code — it’s delivering AI that actually works in business environments. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 & 𝗦𝘁𝗮𝗰𝗸 🔵 Python 🔵 Machine Learning & Deep Learning 🔵 Natural Language Processing (NLP) 🔵 OpenAI & LLM architectures 🔵 Automation frameworks & API integrations Built for scalability, efficiency, and real business value. 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝗱 🤖 𝗔𝗜 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀 & 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 🔵 OpenAI, Dialogflow & custom LLM chatbots 🔵 Customer support, lead generation & workflow bots 🔵 Context-aware, production-ready conversational AI 🧠 𝗡𝗟𝗣 & 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 🔵 Text analysis, classification & entity extraction 🔵 Model debugging, tuning & optimization 🔵 Custom language model solutions ⚙️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 & 𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 🔵 Business process automation 🔵 API integrations & intelligent workflows 🔵 End-to-end AI system architecture 🚀 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 & 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 🔵 Bug fixing & system stabilization 🔵 Speed, accuracy & scalability improvements 🔵 Production deployment readiness 𝗥𝗲𝗮𝗹 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 𝗳𝗼𝗿 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 Clients don’t just get code. They get clarity, speed, and intelligent systems that create growth. 🔵 Reduced manual workload 🔵 Faster operations 🔵 Smarter decision-making 🔵 Scalable AI infrastructure 🔵 Real business efficiency 𝗪𝗵𝘆 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗖𝗵𝗼𝗼𝘀𝗲 𝗠𝗲 🔵 Clear communication 🔵 Clean, maintainable code 🔵 Fast, reliable delivery 🔵 Practical, business-focused AI solutions No unnecessary complexity. Just real AI that works. Let’s Build Something Smart 𝗛𝗮𝘃𝗲: 🔵 An AI idea 🔵 A business problem 🔵 A workflow needing automation 🔵 A chatbot or NLP system to build 𝗦𝗲𝗻𝗱 𝗺𝗲 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲. I’ll provide a clear solution, practical roadmap, and fast execution plan. Let’s create intelligent, scalable, future-ready AI systems together. 𝐘𝐨𝐮 𝐦𝐚𝐲 𝐜𝐨𝐦𝐞 𝐚𝐜𝐫𝐨𝐬𝐬 𝐦𝐲 𝐩𝐫𝐨𝐟𝐢𝐥𝐞 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐭𝐡𝐞𝐬𝐞 𝐤𝐞𝐲𝐰𝐨𝐫𝐝𝐬: AI Developer | AI Engineer | Artificial Intelligence Engineer | Machine Learning Engineer | Deep Learning Engineer | NLP Engineer | Natural Language Processing Engineer | Python Developer | Python AI Developer | Large Language Model Developer | LLM Developer | Generative AI Developer | OpenAI Developer | ChatGPT Developer | GPT Developer | Claude AI Developer | Gemini AI Developer | DeepSeek Developer | AI Chatbot Developer | Conversational AI Developer | AI Agent Developer | Autonomous AI Agent Developer | Multi Agent AI Developer | Agentic AI Developer | AI Automation Expert | Workflow Automation | Business Process Automation | Intelligent Automation | AI Integration Specialist | AI Consultant | AI Solutions Architect | AI Software Developer | AI Application Developer | AI SaaS Developer | Enterprise AI Developer | Custom AI Solutions | AI MVP Developer | AI Product Developer | Prompt Engineer | Prompt Engineering | Retrieval Augmented Generation Developer | RAG Developer | Semantic Search Developer | Knowledge Base Chatbot | Document AI | PDF Chatbot | AI Copilot Developer | LangChain Developer | LangGraph Developer | LlamaIndex Developer | CrewAI Developer | AutoGen Developer | Model Context Protocol Developer | OpenAI Agents SDK | OpenAI API Developer | AI API Integration | FastAPI Developer | Flask Developer | Backend AI Developer | REST API Developer | AI Workflow Builder | AI Orchestration | n8n Developer | Make Developer | Zapier Developer | Python Automation | Voice AI Developer | AI Voice Agent | AI Calling Agent | AI Receptionist | Speech to Text | Text to Speech | Whisper Developer | ElevenLabs Integration | AI Customer Support | Customer Support Chatbot | AI Helpdesk | Lead Generation Chatbot | AI Sales

Experienced data scientist with over 4 years of experience in machine learning projects. Active participant on Kaggle, a google backed platform for data science competitions, rated within Top 1% data scientists globally. Have experienced in deep neural networks, convolution neural networks, recurrent neural networks, genetic algorithms, natural language processing, support vector machines, and generative adversarial networks. 𝐒 𝐊 𝐈 𝐋 𝐋 𝐒 ------------------------- 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 : - CNN, - DNN, - RNN/LSTM, - GAN, - Transformers, - Auto-Encoders, - HMM-GMM - SVM, - Boosting, - Random forest, 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - C, - C++, - Python, - R, - Matlab, - CUDA(Beginner). 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸/𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Tensorflow, - Tensorflow lite, - Tensorflow js, - Keras, - Pytorch, - RASA, - Pandas, - Scikit-learn, - Open CV, - Tesseract OCR, - Kaldi, - OpenFace, - SpaCy, - NLTK, - Open Pose, - Others as well based on experience. 𝗧𝗼𝗼𝗹 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 : - Jupyter-notebook - Google Colab - Pycharm - R-Studio 𝗣𝗮𝘀𝘁 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗼𝗿𝗸 : - Generating karyotype from Chromosome micro slide image. - Identify boundaries of wound and measurement of wound - Extensive object detection, Detection of Sky, Window, Glass, Tree, building. - automated tool for detecting norms and stereotypes in popular culture. - Deep Learning with Image processing for the transformation of style from one image to another. - Mobile embedded object detection model with TF-lite. - Developed an algorithm to generate a 3D model of faces from a single 2D mobile selfie using Python, Convolutional Neural Networks, PyTorch, and CUDA. - Created an algorithm for image and video compression using similarity between images with the help of OpenCV. - Developed an algorithm for the classification of different sounds of drones using MFCC and LPCC features and then SVM and HMM-GMM classifiers. - Created a default loan predictor algorithm with 99.4% accuracy using Python and deep neural networks. - Created an optical character recognition for English language using Python and OpenCV,. - Extracted the Legos from the videos and the classify it into 52 different classes using the convolutional neural network using Python. - Worked on the CNN based binary text classification for the movie reviews to identify the positive and negative reviews with neural networks and Python. - Developed an algorithm for moving object detection, which can find a moving object in a vibrant environment using deep neural networks, OpenCV, and Python. - Many other projects I have worked on. Few of them are signed with NDA. I shall be glad to provide any information/clarification that you might need to make a better decision. If you like my work. Please Direct Message me OR invite me to your job. I will happy to connect and take your project to success. Thanks for taking the time to read through my profile. Looking forward to talking to you. Thanks

Hi 👋 I'm Vlad, AI developer with 10+ years of experience in engineering. Top Rated on Upwork, $100K+ earned, 2,900+ hours logged. Sound familiar? - Your team spends hours on tasks that could run automatically - You tried an off-the-shelf AI tool - it doesn't fit your workflow - You have a great product idea with AI at the core, but don't know where to start - Your current chatbot answers FAQs but can't actually do anything - You need AI that works with your existing data, tools, and processes - not around them If any of these sound like your situation, here's what I've built for clients in exactly that spot: 💡 AI financial assistant for WealthFluent (Fintech) - Built on Amazon Bedrock + Claude Sonnet. The assistant handles 100% of new user onboarding through conversation, explains portfolio data in plain English, and stays fully compliant with financial regulations. Zero hallucinations on numbers thanks to a hybrid AI + deterministic logic layer. 💡 AI language learning platform for Skrivanek Group (EdTech) - World's largest ISO-certified language school needed an AI-powered SaaS. We built it in 7 months: OpenAI-driven learning assistant, adaptive exercises across 30+ languages, Stripe subscriptions, full user management. Stack: Next.js, LangGraph, LangSmith, PostgreSQL. 💡 AI goal management coach (Productivity SaaS) - Personal coach PWA built in 3 months. AI breaks goals into milestones, sets reminders, tracks progress. Result: 50% faster task execution for users. 💡 AI platform for insurance brokers (InsurTech) - Modernized the UX of an AI-powered broker tool. Saved 1,500+ hours of broker time annually. Redesigned 10+ core workflows, integrated Stripe credit management and document previews. What I build: - AI chatbots that understand context (not just keywords) - AI agents that execute multi-step workflows autonomously - RAG systems that let AI answer from your company's knowledge base - Generative AI features embedded into SaaS products - AI-powered onboarding, support, and automation flows Tech stack: OpenAI, Anthropic Claude, LangChain, LangGraph, Amazon Bedrock, AWS, Next.js, React, Node.js, Python, PostgreSQL, Stripe Industries: FinTech, EdTech, InsurTech, Healthcare, Manufacturing, Logistics Every project starts with: what problem costs you time or money right now? Then we build exactly what's needed - prototype first, production-ready fast. 🏆 "They value clients and their own time. Excellent time management, understood our needs, set realistic expectations." — Arturs Peha, CSO at Skrivanek Let's talk about your project.

I help founders, startups, and small businesses turn AI ideas into reliable, production-ready systems, not just demos. As a Senior AI Systems Architect with 20+ years in software and ~10 years in production AI, I bring technical leadership and hands-on execution. I previously founded an AI company (2019) and have held CTO and senior engineering roles. Clients hire me when they need someone senior enough to own the full solution: architecture, AI implementation, full-stack development, and long-term maintainability. I specialize in building: • Production AI Agents & multi-agent systems (LangGraph, CrewAI, AutoGen, etc.) • Advanced RAG and private knowledge systems • AI-powered MVPs and full-stack applications (Next.js, React, Node.js/Python, TypeScript) • On-prem/local LLM deployments, GPU infrastructure, and cost-efficient scaling • Secure automation, retrieval systems, and AI platform rebuilds My stack includes OpenAI, Anthropic, LlamaIndex, LangChain, Ollama, PostgreSQL, vector databases, Docker, Tauri, Rust, and major cloud providers. Most of my clients are founders or small teams that need a senior engineer who can act as technical lead or fractional CTO, delivering fast but building something that survives real users, security requirements, latency, and scaling pressure. I focus on systems that are trustworthy and maintainable after launch. If you need senior ownership from architecture and MVP build to production deployment and roadmap I'm a strong fit. I help avoid costly technical debt and short-term thinking that kills AI projects.

𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰 If your Vision AI project must work outside a demo, accuracy alone is not the problem.
Most failures come from deployment constraints, unclear acceptance criteria, and brittle integration.
I build computer vision systems that remain reliable when they meet real cameras, real environments, and real operations. I take projects from ambiguous idea to an engineered deliverable that you can run, verify, and maintain. This includes defining success metrics, selecting the right model class, building the data and training pipeline, and deploying to an edge device or a production server with versioned releases. Clients typically involve me when the work has operational stakes, such as automated inspection, remote sensing workflows, safety monitoring, robotics vision, or IoT enabled automation, where the system must be stable, explainable, and measurable. 𝐖𝐡𝐚𝐭 𝐈 𝐀𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐃𝐨 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐚𝐧𝐝 𝐕𝐢𝐬𝐢𝐨𝐧 𝐀𝐈: detection, segmentation, tracking, event logic, and rule based vision workflows using OpenCV, PyTorch, TensorFlow, YOLO variants, Vision Transformers, and modern segmentation pipelines.
 𝐄𝐦𝐛𝐞𝐝𝐝𝐞𝐝 𝐚𝐧𝐝 𝐄𝐝𝐠𝐞 𝐕𝐢𝐬𝐢𝐨𝐧: deployment on NVIDIA Jetson and Raspberry Pi, camera integration, performance tuning, and reliability hardening, including model optimization when required.
 𝐃𝐚𝐭𝐚 𝐚𝐧𝐝 𝐓𝐢𝐦𝐞 𝐒𝐞𝐫𝐢𝐞𝐬: orecasting, anomaly detection, and production grade analytics pipelines with pandas, NumPy, scikit learn, and Keras when appropriate. 𝐈𝐨𝐓 𝐚𝐧𝐝 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: sensor and controller integration, telemetry, device communication, and automation workflows, including networking and protocol driven integration.
 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 𝐀𝐏𝐈𝐬 𝐟𝐨𝐫 𝐀𝐈 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬: FastAPI, Flask, and Django services for inference endpoints, device management, and analytics.
 𝐑𝐞𝐚𝐥 𝐭𝐢𝐦𝐞 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: socket based systems, SocketIO patterns, and BACnet related integration where the environment requires it. 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: packaging, installation scripts, version control discipline, update strategy, and clear handover documentation. 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐂𝐡𝐨𝐨𝐬𝐞 𝐌𝐞 • I define acceptance tests, failure modes, and operating constraints early, so “done” is unambiguous.
 • I communicate in decisions and trade offs, not in jargon, and I document what matters for maintenance.
 • I design for deployment from day one, including latency, throughput, compute limits, and network realities.
 • I write code that another engineer can maintain, with clean structure, reproducibility, and sensible defaults.
 • I surface risks early to protect timelines, rather than discovering constraints near delivery.
 • I keep scope controlled, while ensuring the system remains extensible as your product evolves. 𝐏𝐫𝐨𝐨𝐟 𝐚𝐧𝐝 𝐂𝐫𝐞𝐝𝐢𝐛𝐢𝐥𝐢𝐭𝐲 In this domain, credibility is demonstrated through deliverables that are runnable, measurable, and maintainable. Depending on your project, you can expect outputs such as: • A reproducible training and evaluation pipeline, with documented dataset assumptions.
 • Results reported for decision making, including class wise metrics and error analysis when relevant.
 • A deployable inference package or service, not only notebooks, with clear run instructions.
 • Integration artifacts such as camera configuration, streaming handling, API contracts, and device communication logic.
 • A structured handover kit, including environment setup, dependency pinning, and a concise maintenance guide. For edge deployments, I also plan for operational realities, including logging, recovery behavior, and an update strategy appropriate for production devices. 𝐖𝐡𝐨 𝐒𝐡𝐨𝐮𝐥𝐝 𝐇𝐢𝐫𝐞 𝐌𝐞 You are a strong fit for working with me if you need a Vision AI system that must run reliably in production, on an edge device, or inside an existing workflow. You value measurable performance, clear acceptance criteria, and an engineering approach that covers data, model, integration, and deployment. I am not the right fit if you only want the lowest cost model training without deployment, documentation, or engineering ownership. I also tend to decline projects where validation is impossible due to lack of representative data, or where scope is intentionally kept fluid while timelines are expected to remain fixed. 𝐍𝐞𝐱𝐭 𝐒𝐭𝐞𝐩 Share a brief description of your use case, your target environment, such as cloud, Jetson, or Raspberry Pi, and what success looks like. I will respond with a concrete plan, key risks to address early, and a practical delivery structure.

Hi there! I'm an AI Engineer specializing in Computer Vision, LLM Fine-Tuning, RAG Systems, and AI Agent Development. With 4+ years of hands-on experience in Machine Learning and AI engineering, I build intelligent, production-ready systems that help businesses automate workflows, analyze visual data, detect sensitive information, and make smarter decisions with AI. ⚙️ What I Do: • RAG & LLM Systems: Production RAG pipelines with semantic search, vector stores (ChromaDB), time-aware retrieval, and grounded LLM responses via OpenAI GPT-4o-mini and LangChain — deployed on GCP with Docker and GitLab CI/CD • LLM Fine-Tuning: End-to-end fine-tuning pipelines across Llama, Mistral, Gemma, Phi, DeepSeek, Qwen, and Granite for NLP classification tasks — including custom dataset construction, HuggingFace Trainer API, and benchmark evaluation • Computer Vision: Real-time object detection and tracking (YOLOv8/v11, ByteTrack, StrongSORT), multi-camera Re-ID with epipolar geometry, emotion recognition, and TensorRT/ONNX-optimized inference pipelines • AI Agents & Automation: LLM-powered agents, Celery-based data ingestion pipelines, chatbot development, and API-driven workflow automation with FastAPI • ML Model Development: CNNs, NLP, model training, fine-tuning, ONNX/TensorRT optimization, and scalable production deployment • AI Infrastructure: FastAPI, Docker, GCP, GitLab CI/CD, PostgreSQL, MongoDB, Redis, scalable AI app architecture 🧠 Tech Stack: Python · PyTorch · HuggingFace Transformers · LangChain · OpenCV · YOLOv8/v11 · ChromaDB · FastAPI · Celery · Docker · PostgreSQL · MongoDB · GCP · GitLab CI/CD · ONNX · TensorRT · Streamlit · Stable Diffusion · scikit-learn 🌟 Why Clients Work With Me: • End-to-end delivery — from data collection and model training to production deployment and maintenance • Hands-on experience across media, retail, urban planning, and data privacy domains • High focus on accuracy, low latency, and scalability • Clear communication, fast delivery, and strong problem-solving under real production constraints Let's bring your AI, Computer Vision, or LLM idea to life 🚀

I provide work to customers with a guarantee of quality and also offer a range of other services with excellence across Python projects in Machine Learning, Deep Learning, and Generative AI. Our motto: Quality, Creativity, and Client Satisfaction. I have been working on various projects that I mention below: ✨ Experience in Machine Learning (Supervised learning, Unsupervised learning, Reinforcement learning) ✨ Experience in Generative AI (LLM-based apps, RAG pipelines, AI Agents, Prompt Engineering) ✨ Experience in Natural Language Processing (Text Classification, NER, Sentiment Analysis, Embeddings) ✨ Experience in Time Series Forecasting (RNNs, LSTM, ARIMA, Prophet, Others) ✨ Experience in Deep Learning (ANN, CNN, RNN, LSTM, GAN, Transformers, Others) ✨ Experience in Computer Vision (Object Detection, Face Recognition, Others) I can also handle any project related to these: ✨ Classification Related Problems ✨ Regression Related Problems ✨ Clustering Related Problems (KMeans, DBSCAN, HDBSCAN, Hierarchical Clustering, Others) ✨ NLP Tasks (Text Preprocessing, Tokenization, Topic Modeling, Text Summarization) ✨ RAG-based Chatbots & Knowledge Assistants (LangChain, LlamaIndex, FAISS, Pinecone) ✨ AI Agents (OpenAI, Claude API, Tool Use / Function Calling, Multi-agent Systems) ✨ WhatsApp / Telegram / Web Chatbots powered by LLMs ✨ Data Analysis (Pandas, NumPy, Others) ✨ Data Visualisation (Matplotlib, Seaborn, Plotly) ✨ Dimensionality Reduction (PCA, LDA) ✨ Reinforcement Learning (Policy, Reward, DQN, Others) ✨ Prediction Related Problems And I will train and predict on your dataset using whichever models suit your problem best, such as: ✨ Artificial Neural Network (ANN) ✨ Convolutional Neural Network (CNN) ✨ Recurrent Neural Network (RNN) ✨ Long Short Term Memory (LSTM) ✨ Transformer-based Models (BERT, GPT-style architectures) ✨ Large Language Models (OpenAI GPT, Anthropic Claude, Open-source LLMs) ✨ Others Whether it's a classic ML pipeline, an NLP system, or a custom AI agent powered by LLMs, I focus on building solutions that are accurate, explainable, and production-ready.

Top-Rated AI/ML Engineer with 7+ years building intelligent, scalable web applications and AI-powered automation systems. I specialize in integrating Large Language Models (LLMs), machine learning pipelines, and conversational AI into production-grade platforms across healthcare, finance, eCommerce, SaaS, and logistics. Core Expertise: - AI/ML Development: Python, TensorFlow, PyTorch, OpenAI API, LangChain, Hugging Face, scikit-learn, RAG pipelines, vector embeddings, prompt engineeringPython, - Chatbots & Conversational AI: AI agent development, NLP, intent classification, multi-turn dialogue systems, automated workflow routing - Full-Stack Development: Ruby on Rails, Node.js, FastAPI, React.js, Vue.js, Angular, REST APIs, GraphQL, microservices - Backend & Databases: PostgreSQL, MySQL, MongoDB, Neo4j, Redis, SQL, NoSQL, scalable architecture - Cloud & DevOps: AWS, GCP, Azure, Docker, Kubernetes, CI/CD, MLflow, Airflow - Automation & Integration: n8n, Zapier, Make(Dot)com, API integrations, webhook handling, ETL pipelines Key Projects: - OmniBot – AI-powered HR automation chatbot processing 10,000+ documents with multi-agent coordination and intelligent routing - AI-Driven PC Part Compatibility Chatbot – ML-based recommendation engine using Random Forest and SVM - Employee Attrition Prediction Chatbot – Predictive modeling with EDA and feature engineering for workforce insights - AI Mechanical Advisor – RAG-based car parts chatbot with intelligent database search and expert recommendations - I deliver end-to-end AI solutions, from data preprocessing and model development to deployment and optimization, combining clean code, modular architecture, and performance-first engineering with cutting-edge AI capabilities. Top-Rated Plus | $400K+ Earned | 100% Job Success | 12,565+ Hours | 0-4 Hour Response Time