Zubayer built our entire AI pipeline from scratch. The NLP system he architected reduced our support load by 60%. Exceptional technical depth and communication.
Md.ZubayerHossainPatowari
Passionate engineer building AI systems that solve real problems — from healthcare automation to multilingual NLP platforms — working with global organizations across 3 continents.
Engineer.Innovator.BuilderofIntelligentSystems.

- Currently@ EVU Inc.
- RoleChief AI Engineer
- StatusOpen to Work
I'm Zubayer — an AI & Machine Learning Engineer with 4+ years of hands-on experience building production-grade intelligent systems. My work spans natural language processing, computer vision, and generative AI, deployed across healthcare, media, and business automation sectors.
Currently serving as Chief AI Engineer at EVU Inc., a venture-backed startup ecosystem with 250+ members, where I architect advanced NLP models, RAG pipelines, and MLOps infrastructure. Previously, I've delivered AI solutions for USAID's Breakthrough ACTION program and international media organizations.
Beyond engineering, I'm a lifelong learner and open-source contributor. I believe AI should be accessible, multilingual, and purposeful — which is why my work consistently bridges technical innovation with real human impact.
TechnologiesIWorkWith
ProfessionalJourney
Chief AI Engineer
at EVU Inc.
Led engineering for a venture-backed startup ecosystem (250+ members). Architected advanced NLP and deep learning systems using TensorFlow, PyTorch, Keras, and Hugging Face. Built AI agents with LangChain, integrated RAG pipelines with FAISS and Pinecone. Established MLOps workflows with Docker and Git-based CI/CD. Directed cross-functional teams across web (React.js, FastAPI), mobile (React Native), and cloud (AWS) projects. Maintained 99.9% system uptime.
AI & Automation Developer
at Dhaka Post
Designed and built BanglaShorts — an AI-powered micro-news platform summarizing Bangladeshi news into 59-word stories. Built web scraping engine and NLP pipeline using BanglaBERT and mT5. Implemented duplicate content detection via Sentence Transformers + cosine similarity. Automated social media publishing via Facebook and Instagram Graph APIs. Reduced news reading time by 70%.
Lead Chatbot Developer
at DGFP / USAID
Designed BanglaGPT — a generative AI chatbot under USAID's Breakthrough ACTION project to assist call center agents with health-related queries. Built robust Bangla NLP models for improved accessibility in family planning support.
SelectedWork

TriState Ride - Full-Stack Luxury Chauffeur Platform (Passenger, Driver & Admin Ecosystem)
Passenger App: Expo (React Native) | Driver App: Expo (React Native) | Super Admin Panel: Next.js + Tailwind CSS | Backend/API: Node.js + Express.js | Database: PostgreSQL / MongoDB | Real-time: Socket.io | Maps: Google Maps API | Auth: JWT + OAuth | Cloud: AWS / GCP | Payments: Stripe
Built and deployed TriState Ride as a complete ecosystem of three connected applications: Passenger App (Expo), Driver/Chauffeur App (Expo), and Super Admin Panel (Next.js). The platform supports on-demand and scheduled bookings, vehicle-class selection, real-time chauffeur tracking, automated assignment, airport transfers, hourly bookings, and cross-state operations across New York, New Jersey, and Connecticut.
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Rolac World Cup Photobooth — AI Football Jersey Generator
Engineered a complete end-to-end system, not just a model demo. A React 18 + Vite SPA handles camera capture, team selection (10 countries) and result download; a Flask API served by waitress (64 threads) behind nginx generates the composite. Google Gemini fuses the selfie and a jersey reference in one pass, backed by a self-hosted CV pipeline (InsightFace buffalo_l + inswapper, ONNX Runtime, MediaPipe segmentation, GFPGAN/OpenCV) with affine alignment, LAB colour matching and seamless blending for direct face/head-swap modes. An admin panel reviews every generated record.
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Face Swiper — Production-Grade AI Face & Head Swap
Built a two-mode pipeline. FACE mode swaps the face while preserving the subject's hairline and surrounding context; HEAD mode performs a full-head transfer. The system uses InsightFace (buffalo_l detector + inswapper) on ONNX Runtime for the core swap, MediaPipe segmentation to isolate regions, affine alignment for geometry, LAB colour matching for tone, and seamless blending to remove seams. GFPGAN restores and upscales facial detail in the final output. Supports group photos and a UI face picker.
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V-TRYON AI — Virtual Clothing Try-On Studio
Built a two-stage AI pipeline. Stage 1 uses SegFormer B2 Clothes to segment upper-body clothing regions (shirt, top, jacket, dress) from the person photo and produce a dilated binary mask. Stage 2 feeds that mask to Stable Diffusion Inpainting with a carefully crafted fashion-photography prompt to generate the new garment realistically onto the body. The person image is resized to 512×768 (Stable Diffusion's sweet spot) and the result is returned as a base64 PNG. A modern dark glassmorphism UI offers drag-and-drop uploads, real-time API health status, progress indicators and one-click downloads.
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PinVault — Secure Internal Vendor Map Platform
Built a full-stack platform with a Node.js + Express + MySQL backend and a fast single-file HTML/Leaflet frontend. Role-based access (super admin vs employee) is enforced with JWT + bcrypt. Vendors can be created from a location search or a direct map click, with fields for description, notes, phone, website, category and coordinates. Super admins manage staff, edit/remove vendors, and import/export data in CSV and JSON, plus export the map as an image. Browser-side privacy deterrents include username/timestamp watermarking, right-click and copy blocking, dev-tools deterrence, and Print-Screen detection with a capture-shield overlay.
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WhatICanBuildForYou
AI & Machine Learning Engineering
End-to-end ML system design, training, evaluation, and production deployment. Specializing in NLP, computer vision, and generative AI systems that solve real business problems.
LLM & Generative AI Development
Custom LLM fine-tuning, RAG pipeline architecture, AI agent development, and chatbot systems using LangChain, OpenAI, Gemini, and Hugging Face. Multilingual support included.
Conversational AI & Chatbots
Production-grade chatbots with context retention, multi-turn dialogue, WhatsApp/call integration, and business workflow automation. Deployed across healthcare, e-commerce, and service industries.
Full-Stack Web Development
Scalable web applications using React, Next.js, FastAPI, and Node.js. REST and GraphQL API design. Cloud deployment on AWS with Docker containerization and CI/CD pipelines.
MLOps & Infrastructure
CI/CD pipelines for ML models, Docker containerization, model versioning, monitoring dashboards, and scalable AWS deployment. Ensuring 99.9% uptime.
Data Science & Analytics
Data pipeline engineering, model evaluation frameworks, business intelligence dashboards, and actionable insights from complex datasets.
WhatClientsSay
Delivered the BanglaShorts platform on time and beyond expectations. The automation saved us hours of manual work daily. A genuinely talented engineer.
His understanding of LLMs and RAG architecture is among the best I've encountered. He translated complex AI requirements into working production systems seamlessly.
We needed a multilingual chatbot for three languages under a tight deadline. Zubayer delivered a production-quality system two weeks early. Truly impressive.
Zubayer redesigned our ML inference pipeline, cutting latency by 40%. His systematic approach to problem-solving and clear communication made the project a pleasure.
From architecture to deployment, every detail was handled with care. The FastAPI backend he built handles 10k+ daily requests without a single issue.
Zubayer built our entire AI pipeline from scratch. The NLP system he architected reduced our support load by 60%. Exceptional technical depth and communication.
Delivered the BanglaShorts platform on time and beyond expectations. The automation saved us hours of manual work daily. A genuinely talented engineer.
His understanding of LLMs and RAG architecture is among the best I've encountered. He translated complex AI requirements into working production systems seamlessly.
We needed a multilingual chatbot for three languages under a tight deadline. Zubayer delivered a production-quality system two weeks early. Truly impressive.
Zubayer redesigned our ML inference pipeline, cutting latency by 40%. His systematic approach to problem-solving and clear communication made the project a pleasure.
From architecture to deployment, every detail was handled with care. The FastAPI backend he built handles 10k+ daily requests without a single issue.
Insights&Writing

How I Built an AI Photobooth That Scales to 30,000 Users on a Single Server
The model is the easy part. Here is the full system architecture — async job queues, bounded worker pools, load shedding and multi-key rotation — that let a Google Gemini photobooth survive 30,000 people uploading selfies at a live football event.
Building Production-Ready RAG Pipelines with LangChain and Pinecone
RAG systems are only as good as their retrieval architecture. Here's how I build pipelines that stay accurate at scale...
BanglaBERT Fine-Tuning: Lessons from Building for Low-Resource Languages
Fine-tuning transformer models for Bangla taught me more about NLP fundamentals than any course. Here's what worked...
Why MLOps Is the Missing Piece in Most AI Projects
Most AI projects fail not because of bad models, but because of terrible deployment practices. Here's the infrastructure checklist I use...
Let'sBuildSomethingIntelligentTogether
Available for full-time roles, freelance projects, and technical consulting engagements.
- mdzubayerhossainpatowari@gmail.com
- +880 1841 606311
- Dhaka, Bangladesh
