Hire the Best YOLO Specialists

🔹 Top Rated Machine Learning Engineer | Expert in Detection, Tracking, Classification & OCR I specialize in building high-accuracy computer vision models — from object detection and classification to keypoint detection and OCR. With deep experience in YOLO (v8–v11), TensorFlow, and PyTorch, I’ve delivered results across industries including healthcare, logistics, and agriculture. 🚀 Highlighted Projects: 🔍 License Plate Recognition & Number Swapping — for Korean and Kazakh vehicles 🏥 COVID-19 & Viral Pneumonia Detection — 95%+ accuracy using X-ray images 🍎 Fruit Detection (Apple, Peach, Potato) — precision object detection with YOLO 📄 OCR & Keypoint Detection — paper/card ID localization and tracking 🏎️ Speed Estimation & Vehicle Tracking — model fusion using YOLO + Deep SORT ⚙️ Core Skills & Tools: YOLOv5/v8 | TensorFlow | PyTorch | OpenCV | ONNX Object Detection, Classification, OCR, Keypoint Detection High-speed model training on RTX 4080 Super As a Top Rated freelancer, I deliver clean, efficient, and production-ready models on time and with clear communication. Let’s bring your vision to life. 📩 Message me — I respond quickly and build fast.

Most computer vision projects fail not in training — but in deployment. Models that hit 95% accuracy in the lab break down when lighting shifts, hardware stutters, or the camera feed isn't clean. I build systems engineered to survive those conditions — and I've done it across industries, hardware platforms, and deployment environments. I'm a Computer Vision Engineer specializing in end-to-end AI pipelines — from raw camera input to real-time inference, deployed on edge hardware, cloud APIs, or both. ━━ Core services ━━ → Object detection & multi-object tracking — YOLOv8, YOLOv5, ByteTrack, BOTSort, MMDetection → Segmentation, pose estimation & keypoints — MediaPipe, custom model architectures → Edge AI deployment — NVIDIA Jetson Orin/Nano, Raspberry Pi, Hailo — TensorRT, ONNX, INT8/FP16 → Cloud & API deployment — FastAPI, Docker, AWS GPU instances, REST & WebSocket inference APIs → Video analytics & smart camera systems — safety monitoring, defect detection, zone tracking, people counting ━━ Systems I've shipped ━━ ✓ Real-time fall detection on NVIDIA Jetson — production-deployed, sub-100ms latency ✓ Zone-based people tracking & monitoring for safety-critical environments ✓ Industrial defect detection pipeline — TensorRT-optimized, running on constrained edge hardware ✓ End-to-end smart camera system: camera → inference → dashboard & real-time alerts ✓ OpenCV video analytics pipelines with custom pre/post-processing and business logic ━━ What makes my work different ━━ Most CV engineers deliver a model file. I deliver a working system — optimized, integrated, and running reliably in your environment. I lead a small team and personally own system architecture, optimization strategy, and core AI engineering on every project. You get senior-level technical execution, not delegation to juniors. Edge or cloud. Jetson or GPU server. Prototype or production scale. I've built across all of it. ━━ How a typical project runs ━━ 1. Discovery — review your hardware targets, data sources, and latency requirements before any code is written 2. Architecture — design the full pipeline: model selection, optimization path, deployment stack, integration points 3. Build & optimize — iterative development with benchmarked FPS and accuracy metrics at each stage 4. Deployment — containerized, documented, and running on your target environment 5. Handover — clean codebase, inline documentation, and a session so your team can maintain it independently ━━ Full tech stack ━━ Models: YOLOv8, YOLOv5, YOLOv7, MMDetection, Detectron2, PyTorch, TensorFlow, ONNX Runtime Tracking: ByteTrack, BOTSort, DeepSORT, StrongSORT, custom zone logic & counting algorithms Optimization: TensorRT INT8/FP16, ONNX quantization, model pruning, batch inference tuning Edge hardware: NVIDIA Jetson Orin/Nano, Raspberry Pi 4/5, Hailo-8, Coral TPU Cloud & infra: FastAPI, Flask, Docker, AWS EC2/Lambda, GCP, RTSP/RTMP stream processing Vision utilities: OpenCV, FFmpeg, GStreamer, PIL/Pillow, custom pipeline components ━━ Project types I take on ━━ → Greenfield CV systems — full pipeline from scratch to production deployment → Model optimization — take an existing model and make it production-fast on your hardware → Edge porting — migrate a cloud-based CV system to Jetson, Raspberry Pi, or Hailo → Pipeline debugging — diagnose and fix latency, accuracy, or stability issues in live systems → Inference API — wrap your CV model as a scalable, low-latency REST or WebSocket API → PoC → production — take a working demo and harden it for real-world deployment at scale → Team augmentation — embedded senior CV engineer for sprints or longer-term engagements ━━ Industries served ━━ Manufacturing & quality control — defect detection, visual inspection, production line monitoring Safety & security — real-time threat detection, perimeter monitoring, crowd analytics Retail & logistics — shelf analytics, people counting, queue management, warehouse tracking Healthcare — patient monitoring support systems, lab automation, medical imaging pipelines Agriculture — crop health detection, drone-based aerial inspection, field monitoring systems ━━ Common questions ━━ Work with our existing dataset? Yes — I assess quality, recommend augmentation strategies, and fine-tune models on your labeled data. Edge or cloud deployment? Both — Jetson, Raspberry Pi, and Hailo at the edge; AWS GPU instances and containerized APIs in the cloud. Can you take our prototype to production? That's one of my most common engagements — hardening, optimizing, and deploying existing concepts for real-world reliability. Documentation and handover included? Always. Clean code, inline comments, deployment instructions, and a dedicated handover session on every project. If you need computer vision that performs beyond lab conditions — on real hardware, with real data, in real-world environments — let's talk.

Computer Vision Expert | YOLO | Object Detection | Tracking | OpenCV | Deep Learning | Jetson | Real-Time Systems | Image/Video Labeling Specialist | Machine Learning | OCR With 5+ years of experience and 150+ successful projects, I help businesses build high-performance Computer Vision and Deep Learning systems for real-world applications. I specialize in Object Detection, Multi-Object Tracking, Image Segmentation, and Real-Time Video Analytics, delivering scalable AI solutions used in production environments. 🚀 What I Can Do For You ✔ Build Object Detection systems (YOLOv8, YOLO11, YOLO26) ✔ Develop Multi-Object Tracking (DeepSORT, ByteTrack, BOT-SORT) ✔ Create Real-Time Video Analytics pipelines ✔ Design Image Segmentation models (U-Net, DeepLabV3+) ✔ Develop Face Recognition & Liveness Detection systems ✔ Build OCR & Document AI solutions ✔ Optimize models using TensorRT, CUDA, GPU acceleration ✔ Deploy AI systems via APIs, Docker, Cloud (AWS), Jetson ✔ Provide high-quality Image & Video Annotation / Labeling 👁 Core Expertise • Computer Vision • Deep Learning • Machine Learning • Object Detection • Image Segmentation • Multi-Object Tracking • OpenCV • YOLO (YOLOv8, YOLOv11, YOLOv26) • Real-Time AI Systems • Video Processing • OCR & Document AI • Data Annotation & Labeling 🧠 Real-World Solutions I Build • Surveillance & Smart Monitoring Systems • Retail Analytics & Customer Tracking • Face Recognition & Identity Verification • Industrial Defect Detection • Medical Image Analysis • Traffic & Vehicle Detection Systems ⚡ End-to-End Development I handle complete AI pipelines: Data Collection → Annotation → Model Training → Optimization → Deployment You get a fully production-ready system, not just a model. 🛠 Tech Stack 🔹 Deep Learning PyTorch, TensorFlow, Keras, CNN architectures, YOLO variants 🔹 Computer Vision OpenCV, MediaPipe, OCR systems, real-time video processing, detection and tracking pipelines 🔹 Machine Learning Scikit-learn, XGBoost, classification, regression, clustering 🔹 Tracking & Optimization DeepSORT, ByteTrack, SORT, TensorRT, CUDA 🔹 Backend & Deployment FastAPI, Flask, Docker, AWS, Jetson 🔹 Languages Python, C++ 💡 Why Clients Hire Me ✔ 150+ successful projects ✔ 100% Job Success (Top Rated) ✔ Real-time, high-performance systems ✔ Scalable & production-ready solutions ✔ Strong optimization (FPS, latency, memory) ✔ Clear communication & fast delivery 📌 Quick Overview 150+ Projects • 100% Job Success • Top Rated 🎯 Computer Vision — YOLOv8/11/26, Faster R-CNN, U-Net 📍 Tracking — DeepSORT, ByteTrack, BOT-SORT ⚡ Real-Time AI — OpenCV, PyTorch, TensorFlow 🧠 Deep Learning — CNNs, Vision Transformers 📄 OCR & Document AI — Tesseract, Google Document AI 🚀 Deployment — TensorRT, CUDA, Docker, AWS, Jetson 📩 Call to Action Looking to build a Computer Vision system, Object Detection model, or Real-Time AI solution? 👉 Send me a message — I’ll help you design the best approach and deliver a scalable, production-ready solution.

Most machine learning projects fail between the prototype and production. I've shipped 47+ that didn't. 🎯 YOLO Detection | 🧍 Pose Estimation | 🏋️ Sports AI | 🛒 Retail AI | 🛡️ CCTV Analytics | 🔄 Tracking | 🧠 ML Pipelines | 🤖 AI Agents | 💬 LLM Integration You have a working concept — or a clear problem involving cameras, video, or image data. The challenge is making it fast, accurate, and stable under real-world conditions. Wrong framework choices. Inference too slow for live video. Models that break the moment lighting, angle, or environment changes. And systems that detect things but can't reason about them or act on them autonomously. That's exactly where most builds stall. I design and build real-time computer vision pipelines that go all the way — from model training to live deployment — and increasingly, from visual perception to autonomous AI agents that understand, decide, and narrate. Object detection · Machine learning · Pose estimation · Multi-camera tracking · Segmentation · Re-identification · Anomaly detection · OCR & ANPR · Optical flow · Depth estimation · LLM-powered reasoning · Agentic decision pipelines While most CV engineers stop at training the model, I go further: → Accelerated inference with TensorRT, ONNX, OpenVINO, and FP16/INT8 quantization (up to 5× faster) → LLM agents layered over CV pipelines for real-time decisions, alerts, and natural language outputs → Mobile deployment via CoreML (iOS) and TFLite (Android) with 10+ live apps shipped → Edge deployment on Jetson, OpenVINO, Apple Neural Engine, and CUDA/cuDNN → End-to-end pipeline: camera input → training → optimization → real-time actionable output Key Accomplishments: ⭐ Generated $5M+ in client revenue ⭐ Delivered 100+ end-to-end computer vision systems ⭐ Successfully launched my own 2 SaaS products ⭐ Real-time sports AI for 7+ sports, improving analytics for 15+ teams ⭐ Mobile AI on iOS (Core ML) & Android (TFLite), powering 10+ apps ⭐ Surveillance, safety, and industrial AI solutions ⭐ Medical imaging AI for 5+ hospitals: tumor detection, ultrasound, test strips ⭐ Model optimization: up to 5× faster inference using FP16/INT8, ONNX, TensorRT, OpenVINO ⭐ Multi-object tracking, re-identification, Model Training 1M+ labelled Dataset ⭐ Agentic CV systems that perceive, reason, and act without human input in the loop If you have read this far, please note that I appreciate you taking the time to learn about me. Personally, it’s been an amazing journey and knowledge exercise to get to this level of competence in AI and software development. Domain Expertise: - Sports & Fitness: athlete tracking, shot detection, scoring automation, drill analysis, pose estimation - Industrial & Workplace: tire defect inspection, PPE compliance, staff monitoring, meter reading, machine vision inspection, automated quality control - Surveillance & Security: ANPR, crowd monitoring, people counting, animal attack detection, exam cheating detection, perimeter security, intrusion detection - Healthcare & Medical: tumor detection, ultrasound processing, test strip analysis, X-ray/CT scan processing, lesion segmentation, medical image annotation - Traffic & Transport: aerial monitoring, traffic flow AI, license plate recognition, vehicle detection, accident detection, parking management - Retail & Business: customer analytics, receipt extraction, retail intelligence, object recognition, shelf monitoring, inventory management Tech Stack: Machine Learning, Deep Learning, YOLOv5, YOLOv8 - YOLO26, Detectron2, DeepSORT, StrongSORT, MMDetection, MediaPipe, OpenPose, PoseTrack, Action Recognition, Semantic Segmentation, Instance Segmentation, OCR, Anomaly Detection, Motion Detection, Object Counting, License Plate Recognition, PyTorch, TensorFlow, TensorFlow Lite, Keras, OpenCV, FastAPI, Flask, Core ML, TFLite, ONNX, TensorRT, OpenVINO, CUDA, Swift, Kotlin, Flutter, Python, C++, AWS, GCP, Azure, Edge Deployment, Mobile AI, Real-Time Inference, Surveillance AI, Aerial Drone Analytics, Video Stream Analytics, AI Automation, LLM Integration (GPT-4o, Claude, Gemini, Groq), AI Agent Frameworks (LangChain, LangGraph, CrewAI), RAG Pipelines, Streaming LLM Inference license plate recognition, aerial drone analytics, surveillance AI, mobile AI, embedded systems, deep learning pipelines, inference optimization, video stream analytics, AI automation, AI for industry 4.0, computer vision pipelines. If your project involves cameras, video, or images — and you need it fast, accurate, fully deployed, and intelligent enough to reason and act autonomously — I am the engineer you are looking for.

I am a Senior AI Engineer with 5+ years of experience building AI-powered applications, intelligent automation systems, and scalable machine learning solutions for real world business environments. I help startups, agencies, and businesses transform ideas into production ready AI products from prototype to deployment. My expertise includes Generative AI, Large Language Models (LLMs), AI Automation, Machine Learning, NLP, AI Agents, Workflow Automation, and custom AI integrations using modern AI frameworks and cloud technologies. What I Can Help You With AI Core Services * Generative AI Application Development * ChatGPT & OpenAI API Integration * Custom AI Chatbots & AI Assistants * Large Language Models (LLMs) * Machine Learning & Deep Learning Solutions * Natural Language Processing (NLP) * AI Agents & Autonomous Workflows * Computer Vision & Image Processing * OCR & Document AI Systems * RAG Pipelines & Vector Database Integration * AI Model Deployment & Optimization * Predictive Analytics & Recommendation Systems AI Automation Services * AI Workflow Automation * Business Process Automation * Customer Support Automation * CRM Automation * Email Automation * Lead Generation Automation * AI Sales & Marketing Automation * No-Code / Low-Code Automation * AI Integration with APIs & Third Party Platforms * Automation using n8n, Make(.)com, and Zapier Technologies & Tools Python, OpenAI API, ChatGPT, LangChain, LlamaIndex, TensorFlow, PyTorch, OpenCV, FastAPI, Docker, AWS, Pinecone, Weaviate, PostgreSQL, REST APIs, Linux, Git, n8n, Make(.)com, Zapier, and cloud based AI infrastructure. Why Work With Me * 5+ years of experience in AI & Automation * Production ready and scalable AI solutions * Strong focus on performance, efficiency, and reliability * Clean architecture and maintainable code * Fast communication and professional collaboration * End-to-end development from idea to deployment You can replace those lines with this stronger and more client-focused ending: I focus on developing scalable AI solutions that improve efficiency, automate workflows, and deliver practical value for businesses. Whether you need AI-powered automation, custom AI applications, machine learning solutions, or intelligent workflow systems, I can help turn your requirements into reliable and production ready solutions. Let’s transform your ideas into smart, scalable AI solutions with powerful computer vision and perception systems designed for real world impact. Best regards, Sana.

I design, optimize, and integrate real-time object detection and tracking pipelines for NVIDIA Jetson, RK3588, and cloud environments — with measurable gains in FPS, latency, and deployment stability. From YOLO training to TensorRT optimization and production integration, I build Computer Vision systems that work reliably on real hardware. If you need more than just a trained model — if you need a working AI system integrated into hardware or software — I deliver complete, production-ready solutions. 🎯 WHAT I DELIVER • End-to-End Deep Learning Pipelines Model architecture → dataset optimization → training → evaluation → deployment • Real-Time Object Detection & Multi-Object Tracking Optimized YOLO pipelines with stable tracking (DeepSORT / ByteTrack / BOT-SORT) • ⚡ Edge AI Acceleration & Performance Optimization TensorRT conversion, CUDA acceleration, latency reduction, memory tuning, FPS improvements • 🔗 AI Integration into Production Systems Jetson deployment, inference APIs, embedded integration, debugging, monitoring & system optimization 🏆 PROVEN EXPERIENCE • 5★ Upwork reviews for NVIDIA Jetson Nano, AGX & Orin deployments • Deployed Frigate and real-time CV pipelines on Jetson Orin NX • Optimized inference performance using TensorRT for improved real-time execution • Installed and configured LLM environments with secure key management & usage tracking • Research & production AI deployment experience at HBrain 🛠 TECH STACK Deep Learning: PyTorch, CNN architectures, YOLO variants Computer Vision: OpenCV, real-time video processing, detection & tracking Optimization: TensorRT, CUDA Systems: Linux, Embedded Systems, NVIDIA Jetson Languages: Python, C++ If you share your hardware target, dataset sample, or performance goal, I can propose a clear technical architecture and realistic delivery plan.