Hire the Best Computer Vision Engineers
in Vietnam

✉️ 𝗙𝗮𝘀𝘁 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲𝘀 | 🌎 𝗧𝗶𝗺𝗲𝘇𝗼𝗻𝗲-𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 | ⚡ 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 I am a highly experienced and versatile Full-Stack Video Streaming and Multimedia Engineer with 8 years of delivering cutting-edge solutions for real-time video, AI, and audio processing. My technical expertise spans low-latency live streaming, computer vision, AI model integration, and professional audio plugin development using frameworks like JUCE and VST. I thrive in designing and deploying scalable, reliable, and high-performance systems that support both multimedia streaming and advanced audio workflows, ensuring seamless experiences across devices, platforms, and use cases. Throughout my career, I have successfully built and optimized complex streaming pipelines supporting 4K content delivery, managing thousands of concurrent viewers globally. I’ve implemented WebRTC-based low-latency conferencing solutions, optimized FFmpeg and GStreamer pipelines for high-quality encoding, and supported adaptive streaming protocols such as HLS, DASH, RTMP, and WebRTC. My experience extends to deploying scalable media servers like Wowza, AWS Elemental, and custom solutions on GCP and Azure, with Docker and Kubernetes for container orchestration, deployment, and scaling. 🛠️ Core Expertise: ✅ Video & Media Processing: FFmpeg, GStreamer, WebRTC, HLS, DASH, RTMP, GPU acceleration (NVIDIA CUDA, Intel Quick Sync), low-latency streaming workflows, and high-quality encoding/decoding pipelines. ✅ Computer Vision & AI: YOLO, OpenCV, TensorFlow, PyTorch, multi-camera object detection, human tracking, pose estimation, AI inference pipelines, and content moderation solutions. ✅ Audio & Plugin Development: JUCE, VST, real-time audio effects, noise reduction, audio analysis, and custom plugin development for professional audio production. ✅ Cloud & Infrastructure: AWS (EC2, S3, Lambda, MediaLive), Azure, GCP, Docker, Kubernetes, Terraform, CI/CD pipelines, and security best practices to ensure scalable, secure, and maintainable deployments. Some of my most notable projects include: ✅ Real-Time Surveillance System: Developed a WebRTC-based streaming solution with YOLO and OpenCV for object detection, deployed on AWS Kinesis, managing 20+ camera feeds at 30 fps with latency under 150 milliseconds. ✅ OTT & IPTV Platform: Architected and deployed an end-to-end IPTV system supporting over 500 channels with adaptive bitrate streaming, reducing bandwidth consumption by up to 40% while maintaining high quality. ✅ Professional Audio Plugins: Designed and implemented VST plugins for advanced audio effects, used by professional studios and musicians worldwide, supporting real-time processing with minimal latency. ✅ Video Analytics & Content Moderation: Built AI pipelines supporting multi-camera tracking, automated content filtering, and real-time alerts for security and media management solutions. ✅ Ad Insertion & Monetization (SSAI/CSAI/DAI): Enhanced ad fill rates by 25% using AWS MediaTailor for SSAI, created a custom HLS/DASH ad stitcher using FFmpeg + Node.js, and integrated Google IMA, FreeWheel, and SpotX for AVOD platforms. ✅ DRM & Content Security: Successfully implemented multi-DRM solutions that reduced piracy leaks by 85%, used AWS KMS and ExpressPlay for dynamic license delivery, and secured live sports streams using AES-128 encryption and tokenized CDN access. 💡 Ready to get started? Let’s bring your ideas to life! 🎯 Feel free to reach out so we can discuss your project and explore how I can help you achieve success. 📩 🟢 Press the "𝗜𝗻𝘃𝗶𝘁𝗲" button and let's discuss your project! 🔑 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀: #WebRTC, #FFmpeg, #Video Stream, #HLS, #RTMP, #DRM, #OTT, #Computer Vision, #GStreamer, #Video Processing, #YOLO, #Node.js, #Python, #React, #Next.js, #GCP, #GraphQL, #REST API, #OpenCV, #TensorFlow, #PyTorch, #Docker, #Kubernetes, #Terraform, #CI/CD, #C, #C++, #Live Stream Customization, #Real Time Stream Processing, #Websockets, #Wowza Media Server, #VoIP, #FreeSWITCH, #Twilio, #Supabase, #PostgreSQL, #MongoDB, #IPTV, #tvOS, #React Native, #Flutter, #Dart, #3CX, #Kamailio, #FreePBX, #Asterisk, #Microservice, #Objective-C, #LiveKit, #Object Detection, #Object Tracking, #Deep Learning, #Robot Operating System, #Machine Learning, #TensorFlow, #Tesseract OCR, #NVIDIA Jetson, #Amazon Kinesis Video Streams, #Real Time Stream Processing, #Over-the-Top Media

AI Engineer with 5+ years of expertise in computer vision and deep learning. Experienced in leading technical teams, building production ML systems, and implementing MLOps best practices. Passionate about leveraging cutting-edge AI technologies to solve complex business challenges.

If your model isn’t performing well, the problem is often the data — I help fix that. I specialize in data-centric computer vision systems: improving detection accuracy, reducing false positives, refining datasets, and deploying stable real-time AI pipelines on edge and mobile devices. I build end-to-end computer vision workflows from dataset preparation and model training to real-time Android deployment. What I help with: ✓ Reducing false positives and missed detections ✓ Dataset QA, cleaning, validation, and deduplication ✓ Improving label consistency across large-scale datasets ✓ Building feedback loops between model predictions and dataset correction ✓ Embedding-based similarity and clustering for duplicate detection ✓ Segmentation mask processing and structured object extraction ✓ Real-time object detection and tracking systems ✓ Improving tracking stability and frame-to-frame consistency ✓ Edge/mobile AI inference optimization ✓ Real-time Android deployment workflows Real-world experience: ✓ Built and deployed computer vision systems for fitness applications ✓ End-to-end pipeline development: dataset preparation → training → inference → Android deployment ✓ Real-time on-device inference pipelines ✓ Barbell tracking and repetition counting ✓ Skeleton-based motion analysis ✓ Equipment classification and tracking consistency ✓ Turning raw detections into stable, usable systems Technical stack: ✓ YOLO (training, fine-tuning, evaluation) ✓ OpenCV, PyTorch, Ultralytics YOLO, SAM ✓ TensorFlow Lite (TFLite) and ONNX deployment workflows ✓ Android Studio, CameraX ✓ CVAT, Label Studio, Roboflow, Labelbox, Supervisely ✓ QGIS, GeoTIFF, GeoJSON, MultiPolygon

Hello, I'm Tam 👋 - 7+ years of experience in Deep Learning, Computer Vision, LLM, and Generative AI. - 3+ years of experience in AI Automation, RAG, AI Agents. - Tech stack: Python, PyTorch, TensorFlow, OpenCV, FastAPI, Docker, CUDA, AWS, Modal, DeepStream, Javascript/TypeScript, NodeJS, NextJS, ReactJS, Electron, Tauri, PyQt - Built high-performance real-time object detection systems with NVIDIA DeepStream for edge and GPU deployment. - Developed OCR & document understanding pipelines for scanned documents, engineering drawings, and forms. - Built LLM/VLM-powered AI applications, including multimodal assistants, RAG systems, image analysis, and AI inference APIs. Let's turn your AI idea into a production-ready product.

🔹 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!

Real-time Computer Vision & Edge AI engineer with a deep C/C++ systems and embedded background. I build AI that runs live on real hardware - not just in notebooks. My focus is real-time video analytics on the edge: object detection, tracking, recognition, and TensorRT/CUDA optimization deployed on devices like NVIDIA Jetson. A strong C/C++, embedded, and Linux systems foundation means I care about the whole system - latency, memory movement, post-processing, UI smoothness, deployment, and failure cases - not just model accuracy. I also build LLM-powered applications that connect models to tools, documents, APIs, and business workflows (RAG, tool calling, automation). Recent work - VisionGuard AI: real-time retail shelf recognition on Jetson Orin NX - Live RTSP video analytics on edge hardware - Dense product detection with GPU-side post-processing - Stable object tracking across frames - Embedding-based SKU recognition - Unknown-product rejection instead of forced labels - Runtime recognition updates without restarting the camera stream - Smooth UI overlay under dense shelf conditions I can help with: - Real-time computer vision systems - YOLO / custom detection pipelines - TensorRT, CUDA, Jetson optimization - Multi-camera RTSP video analytics - Edge AI deployment and debugging - LLM apps with RAG, tool calling, and workflow automation - Python/C++ AI backend integration Core stack: C++ - Python - Qt6 - TensorRT - CUDA - YOLO - OpenCV - RTSP - NVIDIA Jetson - Linux