I help businesses build practical AI/ML systems, evaluate model performance, and create reliable Python-based data pipelines. My work focuses on helping clients move from messy data, manual processes, or early AI ideas to clean, measurable, and production-ready systems. Whether you need a machine learning model, data pipeline, forecasting workflow, model evaluation process, or Python-based automation, I can help you design and build a solution that is clear, reliable, and useful. I can help with: * Machine learning model development and evaluation * AI/LLM workflow testing and response evaluation * Data cleaning, transformation, and analysis * Python-based automation and backend workflows * Data pipelines for structured and unstructured data * Forecasting and prediction models * Classification, clustering, and anomaly detection * Dashboard-ready datasets and reporting workflows * API integration and model output processing I focus on practical implementation, not just technical experiments. My goal is to help you build systems that are accurate, easy to understand, maintainable, and useful for real decision-making. I work with Python, SQL, R, machine learning libraries, data visualization tools, and cloud-based data workflows. I can also support projects involving model monitoring, prompt testing, evaluation metrics, data validation, and process automation. If you are looking for someone who can connect AI/ML, data engineering, model evaluation, and Python development into one practical solution, I would be happy to help.

I architect, build and deploy production-grade agentic AI systems, enterprise RAG platforms and document-intelligence applications using Python, FastAPI, LangGraph and privately hosted or managed LLMs. ✅ 9+ years in AI and machine learning engineering ✅ Upwork Top Rated with 100% Job Success ✅ Completed and delivered projects for global clients ✅ Ranked in the Top 10% of Kaggle competitors ✅ Worked with teams across the North America, Europe and East Asia ✅ Reduced manual review time by 50% and improved retrieval relevance by 35% in production. My work includes enterprise architecture-review agents, regulated document-verification platforms, multimodal intake systems and source-grounded assistants that analyse complex files and return structured findings with citations. CORE CAPABILITIES • Multi-agent architecture and stateful orchestration • Enterprise RAG, document intelligence and multimodal analysis • Evaluation datasets, guardrails and regression testing • FastAPI, PostgreSQL, pgvector and asynchronous processing • Private LLM deployment with vLLM and Kubernetes • Model routing, inference optimization and observability Most AI systems do not fail because the model is incapable. They fail because nobody defines what a correct result looks like. I establish the evaluation dataset and acceptance criteria early, test releases against them, guard inputs, outputs and tool calls, and require human approval before consequential actions. 🧠 PRODUCTION MULTI-AGENT SYSTEMS With LangGraph, I implement state machines, parallel specialist agents, conditional routing, retries, escalation, human checkpoints and PostgreSQL-backed persistence. A long-running job can resume from its last checkpoint instead of restarting after a failure. I use the OpenAI Agents SDK for specialist handoffs, agents as tools, session memory, guardrails and tracing. I use Google ADK with Gemini and Vertex AI when the system must operate inside a client’s Google Cloud environment. A system may include a coordinator, parallel specialists, a reducer that resolves conflicting findings, a citation verifier and a human-review gate for low-confidence decisions. 📚 ENTERPRISE RAG & DOCUMENT INTELLIGENCE I build source-grounded systems over policies, presentations, contracts, technical submissions and scanned files. Retrieval pipelines can include layout-aware OCR, structure-aware chunking, dense embeddings, BM25, Reciprocal Rank Fusion, cross-encoder reranking, page-level citations and abstention when evidence is weak. Hybrid retrieval finds both semantic meaning and exact identifiers such as clause numbers, batch numbers, product codes and case IDs that pure vector search can miss. 🚀 PRIVATE LLM DEPLOYMENT & OPTIMIZATION I deploy LLMs through managed providers, private cloud and self-hosted GPU infrastructure. This includes vLLM on Kubernetes, OpenAI-compatible endpoints, model routing, streaming, batching, asynchronous processing, retries, circuit breakers, caching and token, latency and cost monitoring. I select models based on measured quality, privacy, latency and cost instead of using the largest model for every task. 🛡️ EVALUATION, GUARDRAILS & RELIABILITY I make AI applications measurable and reliable through: • Failure taxonomies built from production traces • Golden datasets with expected answers and source spans • Retrieval, groundedness and citation evaluation • CI regression tests and structured-output validation • Hallucination, contradiction and prompt-injection testing • Repair, retry, fallback, escalation and safe-refusal paths • Token, cost and latency dashboards 📌 SELECTED EXPERIENCE REGULATED DOCUMENT VERIFICATION Built a hybrid retrieval system combining OCR, layout parsing, dense search, BM25, Reciprocal Rank Fusion and reranking. LangGraph agents reviewed technical submissions in parallel and returned evidence-backed findings. A private 32B model ran on Kubernetes through vLLM because documents could not leave the network. ENTERPRISE GOVERNANCE INTAKE Developed a FastAPI and LangGraph platform that checks submissions against internal standards and returns structured findings with evidence. It includes persistent state, parallel review, retries, escalation, human checkpoints, multimodal analysis and pluggable guardrails. 🔌 WORKFLOW & SYSTEM INTEGRATION When an AI system needs Gmail, Google Calendar, Drive, Slack, CRM or internal-system connectivity, I use APIs, webhooks, n8n or custom Python services. n8n is an optional integration layer. Critical reasoning and validation remain in testable, version-controlled Python. STACK Python, FastAPI, LangGraph, OpenAI Agents SDK, Google ADK, Gemini, Claude, Azure OpenAI, n8n, PostgreSQL, pgvector, Redis, Docker, Kubernetes, vLLM, Langfuse, OpenTelemetry, AWS, Azure, GCP and Vertex AI. Send me what is slow, unreliable or difficult to scale. I will respond with a practical architecture, an honest estimate and a clear recommendation.

🔹 AI Engineer | Computer Vision | Edge AI | GPU Optimization | C++ Developer I’m an experienced AI Engineer specializing in Computer Vision with 5+ years of hands-on experience in: ✅ Image & Video Processing – OpenCV, custom algorithm development, real-time analytics ✅ Deep Learning Models – building, training, and deploying models to production ✅ Nvidia GPU Optimization – accelerating inference for high-performance applications ✅ C++ Application Development – real-time AI inference apps on edge devices (e.g., face recognition, posture monitoring, video analytics) ✅ Edge AI Deployment – converting & deploying models on Raspberry Pi, Jetson Nano, Jetson Orin for production-level solutions ✅ Android and iOS models development- training, converting, and implementing inference native code that runs on the device ✅ LLMs & MCP – experience working with large language models and advanced AI systems 💡 I’ve worked on projects ranging from self-driving cars to face recognition systems, always focusing on creating practical, real-world solutions. ✨ What you can expect when working with me: Clean, efficient, and optimized code (Python & C++) End-to-end AI solutions: from research & prototyping to deployment Clear communication and a collaborative mindset I’m passionate about solving complex problems with AI and enjoy working with clients who want to bring cutting-edge technology into real-world applications. 🚀 Let’s work together to turn your idea into a production-ready AI solution!

⭕Upwork Top 10% Freelancer⭕ ⭕100% Customer Satisfaction⭕ I help businesses implement Generative AI to automate workflows, build intelligent chatbots, and integrate AI into real products. My work focuses on LLMs, RAG architectures, AI agents, and automation pipelines — designed for production use, not experiments. What I Build LLM & RAG systems for internal tools and customer-facing applications AI chatbots & assistants powered by GPT and open-source models AI automation for operations, data workflows, and decision support API-based AI services using Python, FastAPI, and Docker Why Clients Choose Me Clear understanding of business use cases Clean, scalable AI system design Fast execution with practical results Strong communication from start to delivery If you’re planning to adopt GenAI, build an AI chatbot, or automate processes using LLMs, send an invite and let’s talk.

Hi there, I’m a Machine Learning Engineer with hands-on experience building, scaling, and deploying AI-driven solutions for businesses of all sizes — from startups to enterprise-level companies. 🚀 I specialize in transforming raw data into real business value through state-of-the-art Machine Learning , Data Science , Deep Learning , Natural Language Processing , Computer Vision , and Generative AI models. Whether you need to develop a recommendation system, fine-tune a Large Language Model, build a custom chatbot, or implement RAG-based AI pipelines, I provide end-to-end solutions in Chatbot Development , AI Agent Development , and AI App Development . My expertise includes: ✔ Natural Language Processing (NLP): text classification, sentiment analysis, summarization, embeddings, topic modeling ✔ Large Language Models (LLMs): fine-tuning, prompt engineering, agentic AI, RAG pipelines ✔ Computer Vision (CV): image recognition, object detection and tracking, OCR , YOLO , OpenCV ✔ Machine Learning & Deep Learning: supervised & unsupervised learning, time-series forecasting, anomaly detection, Neural Network ✔ Data Engineering & MLOps: feature engineering, data pipelines, deployment with Docker/Kubernetes, cloud ( Amazon Web Services , GCP , Azure ) ✔AI App Development & AI Agent Development : building intelligent applications and chatbots, integrating models via API ✔ Tech Stack: Python , TensorFlow , PyTorch, Scikit-learn, HuggingFace, LangChain , OpenAI API 🎯 My goal is simple: deliver reliable, scalable, and efficient AI/ML solutions that help clients achieve measurable results. Ready to integrate cutting-edge AI into your business? Let’s connect and discuss how I can bring your ideas to life.

Your go-to fullstack AI engineer and workflow automation expert, I build AI systems that quietly run in production. Specializes in building AI systems that are: → Helps real Business Operations → Scalable → Enterprise-grade → Multi-tenant → Secure → Built for ROI AI Agents, n8n workflows, LLM multi-agent architecture, RAG pipelines, and the fullstack apps that wrap around them. RECENT WORK: → Multilingual cancellation management system for a German B2B client, Azure OpenAI + n8n classifying vendor replies in German and English, auto-generating bilingual responses. Replaced a manual triage queue. → Mobile Application for a Saudi Arabia Client to manage workforce & work with AI integrations. → End-to-end content automation pipeline, content brief to published post, GCP OAuth, multi-stage n8n workflow. → Outbound sales engine using Apollo + Saleshandy + n8n + Claude API, enrichment, personalization, and reply handling at scale. → Multi-agent HR ops system with Web Application, specialized AI agents handling recruitment, onboarding, and policy workflows across Slack and Teams. → RAG pipelines for B2B catalogs and knowledge bases (HVAC technical specs, internal docs, support corpora) using Pinecone, pgvector, LlamaIndex, and LangChain. → Fullstack SaaS builds, multi-tenant platforms with React/Next.js frontends, FastAPI/Django backends, and AI features baked into the core product flow. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHERE I'M STRONGEST 1. Workflow Automation Production n8n architecture, the messy real-world kind with retries, error handling, rate limits, and observability. Not happy-path demos. Multi-system orchestration across CRMs, email, Slack, databases, and internal APIs. 2. AI Agents & LLM Systems RAG pipelines that retrieve the right thing the first time. Multi-agent orchestration with Anthropic, OpenAI, and open models. Tool use, function calling, evaluation, and production guardrails. Vector databases, embedding strategy, and retrieval tuning. 3. Fullstack Development React and Next.js on the frontend. Python (FastAPI, Django, Flask) and Node.js on the backend. PostgreSQL, MongoDB, vector DBs. REST and GraphQL APIs. End-to-end app delivery, not just the AI layer, but the dashboards, admin panels, auth, billing, and UI your users actually touch. 4. Infrastructure & Deployment Docker, CI/CD pipelines, AWS and Azure. Production monitoring, logging, and the boring reliability work that separates a demo from a system you can bill clients on.

𝗔𝗜 𝗔𝗨𝗧𝗢𝗠𝗔𝗧𝗜𝗢𝗡 𝗘𝗡𝗚𝗜𝗡𝗘𝗘𝗥 & 𝗙𝗨𝗟𝗟-𝗦𝗧𝗔𝗖𝗞 𝗗𝗘𝗩𝗘𝗟𝗢𝗣𝗘𝗥 ✅ 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗣𝗹𝘂𝘀 ✅ 𝟭𝟬𝟬% 𝗝𝗼𝗯 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 ✅ 𝟏𝟏+ 𝘆𝗲𝗮𝗿𝘀 𝐀𝐛𝐨𝐮𝐭 𝐌𝐞 I build AI systems that replace real manual work inside real businesses, not prototypes that need babysitting. I've shipped voice agents, decision automation, outreach systems, and full products across healthcare, fintech, legal tech, and enterprise, working directly with founders from the first idea to paying users. 𝐀𝐈 & 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 ---------------------------------------------------------------------------------------------------------- -Agentic AI Applications: tool-calling agents, memory-augmented agents, autonomous task execution -Multi-Agent Workflows: CrewAI, AutoGen, LangGraph -RAG: LangChain, LlamaIndex, Pinecone, Qdrant, ChromaDB, FAISS -LLMs: GPT-4o, Claude 3.5/4, Gemini, Amazon Bedrock, Ollama -MCP (Model Context Protocol) -Generative AI / GenAI Applications -Semantic Search & Knowledge Bases -AI Chatbots, Copilots & Custom Assistants -Prompt Engineering (multi-turn, few-shot, zero-shot, RAG-based) -LLM Fine-tuning: LoRA, QLoRA, Hugging Face 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 -------------------------------------------------------------------------------------------------------------- -n8n, Make, Zapier, Trigger -AI Workflow & Business Process Automation -CRM Automation, AI SDR Systems, Lead Qualification -Customer Support Automation -API Integrations & Webhooks 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 ------------------------------------------------------------------------------------------------------------- -Vapi -Retell AI -ElevenLabs -Twilio 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 ------------------------------------------------------------------------------------------------------------- -Frontend: React, NextJS, TypeScript, Tailwind CSS, React Native -Backend: Python, FastAPI, NodeJS, NestJS, DotNet, REST APIs, GraphQL -Databases: PostgreSQL, MongoDB, Redis, Supabase -Cloud & DevOps: Azure OpenAI, Azure AI Foundry, AWS, Docker, CI/CD Pipelines, Vercel -AI Dev Tools: Cursor, Copilot, AI SDK 𝐖𝐡𝐚𝐭 𝐈 𝐓𝐲𝐩𝐢𝐜𝐚𝐥𝐥𝐲 𝐁𝐮𝐢𝐥𝐝 -AI SaaS Platforms -AI Agents & Multi-Agent Systems -RAG Applications & Knowledge Bases -Voice AI Solutions (Vapi, Retell AI) -Workflow & Business Process Automation -Enterprise Dashboards & Internal Tools -CRM Integrations & AI SDR Systems -Full-Stack Web & Mobile Applications -Backend APIs & Microservices 𝐇𝐎𝐖 𝐖𝐄 𝐖𝐎𝐑𝐊 𝐓𝐎𝐆𝐄𝐓𝐇𝐄𝐑 ~Fixed-Scope Projects: Best when the deliverable is clear. I send a proposal with timeline, milestones, and ROI before we start. ~Hourly Contracts: Best for ongoing builds and iteration. Weekly check-ins, transparent time tracking. ~Long-Term Retainers: Best when you need a dedicated AI engineer embedded with your team. 40+ hrs/week available. 𝐇𝐎𝐖 𝐖𝐄 𝐆𝐄𝐓 𝐒𝐓𝐀𝐑𝐓𝐄𝐃 _Send a message with what you're trying to fix or build. _Free 20-minute scoping call to align on goals and constraints. _I propose the right engagement model: fixed, hourly, or retainer. _We build, ship, and document; you own everything. Keywords LangChain · LlamaIndex · LangGraph · RAG · Vector DB · Pinecone · Qdrant · ChromaDB · GPT-4o · Claude API · Gemini · Bedrock · Ollama · GenAI · LLM Applications · CrewAI · AutoGen · Multi-Agent · Agentic Workflows · MCP · n8n · Make · Zapier · Vapi · Retell AI · ElevenLabs · FastAPI · NextJS · NestJS · Supabase · Docker · CI/CD · Vercel · AI SaaS · AI Automation · Full-Stack Development

As a dedicated Data Scientist with hands-on experience in developing AI-driven solutions, predictive modeling, and data analysis, I am enthusiastic about collaborating with clients on Upwork to deliver data-driven solutions that propel businesses forward. My diverse skill set and commitment to staying at the forefront of industry trends make me a valuable asset for projects seeking innovation and impactful outcomes. ✔ Successfully developed and deployed an AI conversational chatbot using the ChatGPT model from OpenAI, enhancing customer engagement and support. ➡Tools: Python, Openai ChatGPT, NLTK, Spacy, Pandas, Pinecone Database. ✔Orchestrated the deployment of a machine learning pipeline for a Pricing model using Microsoft Azure cloud environment, ensuring scalability and efficient model operations. ➡Tools: Python, Scikit-learn Random Forest Regressor, Pandas, XGBoost, Matplotplib, Seaborn, Azure ML Studio ✔Maintained and enhanced internal web applications (Oneanalytics and Sterling Data Connect) built with Django and Flask frameworks, showcasing a commitment to delivering user-friendly solutions. ➡Tools: Python, Django, Flask, Javascript, HTML and CSS ✔Built credit risk models and predictive churn models at Accion Microfinance Bank, leading to an 8% improvement in loan portfolio quality and enhanced customer retention strategies. ➡Tools: Python, Scikit-learn Random Forest Classifier, XGBoost, Matplotplib, Seaborn ✔Utilized KMeans clustering algorithm to construct customer segmentation models, driving targeted marketing campaigns and personalized customer experiences. ➡Tools: Python, Scikit-learn KMeans, Matplotplib, Seaborn ✔Developed impactful dashboards using Microsoft Power BI for monitoring business key performance indicators, fostering data-driven decision-making. ➡Tools: Microsoft PowerBI, SQL and DAX

I'm a full-stack AI Engineer who takes projects from idea to production whether that's a real-time computer vision system, an LLM-powered SaaS product, or an automated AI workflow. I've built and deployed solutions for startups and enterprises across healthcare, surveillance, drones, industrial automation, and retail. 🔍 Computer Vision Object detection, tracking & segmentation (YOLOv8, Faster R-CNN, DeepSORT, ByteTrack) Pose estimation, OCR/Document AI, medical imaging, industrial inspection Edge deployment on NVIDIA Jetson with TensorRT, ONNX, INT8/FP16 quantization 🧠 LLMs & Generative AI RAG pipelines with LangChain, LlamaIndex & vector databases (Pinecone, Qdrant, ChromaDB) Fine-tuning & prompt engineering (OpenAI, Claude, Llama, open-source models) AI agents & multi-agent systems (LangGraph, CrewAI, function calling) Multimodal AI — vision + language models for intelligent applications ⚙️ AI Automation & SaaS Workflow automation with n8n, Make & Zapier — connecting AI to your business tools Full AI SaaS development: FastAPI/Flask backends, Next.js frontends, Stripe integration Chatbots, voice AI, and custom AI assistants for web and WhatsApp/Telegram 🚀 MLOps & Deployment Docker, Kubernetes, CI/CD, AWS & GCP Real-time inference APIs, MLflow tracking, scalable cloud + edge architectures What you get: clean code, clear documentation, honest communication, and a system that actually works in production — not just a demo notebook. 📩 Message me and let's scope your project.

⭐⭐⭐⭐⭐ AI/ML Engineer | 100% Job Success | Computer Vision, Recommendation Systems, AI-powered Insights, Chatbots, LLMs and RAG Systems Hi! I'm Ali Raza, an AI/ML Engineer with deep expertise in Computer Vision and Large Language Models. I build and deliver production-grade AI systems that drive real business results—from custom vision models to intelligent RAG pipelines ready for deployment. My focus is delivering fast, scalable, and reliable AI systems that integrate seamlessly into real-world products. 🏅 Expert in Tensorflow, PyTorch, LangChain and Production-Ready AI Solutions ⭐ 100% Job Success | Building Scalable Computer Vision Systems and Chatbots for Startups and Businesses 🏆 Specialized in Computer Vision, LLM Applications, and RAG Pipelines ✔ AI/ML Engineer specializing in Computer Vision ✔ LLM and RAG Systems Architect ✔ Python Backend and AI Integration Expert 👁️ Computer Vision Engineering and Development ___________________________________________________________________________ ✔ Object Detection, Segmentation, and Classification ✔ Image-to-Image Systems | Image and Video Processing ✔ Image Recognition, Image Matching, and Colour Matching Systems ✔ Video Analytics and Real-Time Tracking ✔ OCR and Document Processing Pipelines using Tesseract, OpenCV ✔ Custom PyTorch and OpenCV Model Development ✔ High-Performance Inference and Deployment ⚙️ LLMs and RAG Systems ___________________________________________________________________________ ✔ ChatGPT-like Applications and Custom AI Assistants ✔ Retrieval-Augmented Generation (RAG) Pipelines ✔ Vector Database Integration (PgVector, FAISS, Pinecone) ✔ LangChain-based LLM Workflows and Orchestration ✔ Prompt Engineering and Fine-Tuning ✔ Private Document Q&A and Knowledge Systems 🔨 AI-Powered Backend Systems ___________________________________________________________________________ ✔ FastAPI and Python AI Microservices ✔ REST API Development and Integration ✔ Real-time Inference Pipelines ✔ Scalable Backend Architecture for AI Products 📊 Data Engineering for AI Systems ___________________________________________________________________________ ✔ Data Cleaning, Preprocessing, and Feature Engineering ✔ ETL Pipeline Development and Automation ✔ Data Ingestion and Transformation Pipelines ✔ SQL, PostgreSQL, and MongoDB Database Design ✔ Web Scraping and Large-Scale Document Parsing using Playwright, BeautifulSoup 📩 MLOps and Deployment ___________________________________________________________________________ ✔ Docker Containerization ✔ AWS and GCP Deployment ✔ Model Optimization using ONNX and CUDA ✔ Production Deployment and Scaling ✔ CI/CD and Automation for ML Pipelines 🏆 Key Computer Vision Achievements ___________________________________________________________________________ ✨ Built custom object detection models using YOLO, PyTorch, and OpenCV ✨ Fine-tuned vision models using LoRA for efficient domain adaptation ✨ Developed image similarity and matching systems for visual search ✨ Implemented OCR pipelines for automated invoice and document processing ✨ Designed and deployed real-time video processing systems ✨ Containerized and deployed vision APIs on AWS and GCP infrastructure ✨ Optimized models using ONNX, TensorRT, and CUDA for faster inference ✨ Created automated data extraction pipelines for document-intensive workflows 🛠️ TECH STACK ___________________________________________________________________________ ➡️ Core Languages: Python, SQL, C/C++, JavaScript ➡️ Machine Learning Models and Architectures: ML Models: Logistic Regression, Decision Trees, SVM, KNN, Ensemble Methods, PCA, Naive Bayes Deep Learning: CNNs, RNNs, Autoencoders, GANs, Transformers, Large Language Models (LLMs), UNet, YOLO ➡️ Machine Learning and AI: PyTorch, TensorFlow, Scikit-learn, OpenCV, Keras, ONNX Runtime, Sentence-Transformers, spaCy, NLTK, Tesseract OCR, NumPy, XGBoost, LSTM, Transformer Models ➡️ Model Fine-Tuning and LLM Adaptation: LoRA, QLoRA, Transfer Learning, Fine-Tuning LLMs (GPT, LLaMA, Mistral), Instruction Tuning, Supervised Fine-Tuning (SFT), Adapter Layers ➡️ LLM and RAG Frameworks: LangChain, FastAPI, PgVector, FAISS, Pinecone, Vector Databases, Embedding Pipelines ➡️ Backend and APIs: FastAPI, Flask, REST APIs, Microservices Architecture, Streamlit, Uvicorn ➡️ Data Engineering and Databases: PostgreSQL, MongoDB, MS SQL Server, Neo4j, PgVector, Pandas, NumPy, ETL Pipelines ➡️ Cloud and DevOps: AWS, GCP, Docker, CI/CD Pipelines, Model Serving, Scalable Deployment ➡️ Automation and Scraping: Playwright, BeautifulSoup, Automated Data Extraction, Document Parsing 🤝 Let's Work Together! ___________________________________________________________________________ If you're building an AI product, integrating LLMs, or developing Computer Vision systems, feel free to invite me to discuss your project!