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𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐘𝐨𝐮𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐰𝐢𝐭𝐡 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐑𝐞𝐚𝐝𝐲 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 | 𝟓𝟎+ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 I am an AI/ML engineer specializing in end-to-end artificial intelligence development — from concept to deployed, scalable systems that solve real business problems. With 8+ years building machine learning, deep learning, and generative AI solutions for global clients (including Huawei and Turing), I deliver reliable, production-grade systems — not just prototypes. 𝐖𝐡𝐚𝐭 𝐒𝐞𝐭𝐬 𝐌𝐞 𝐀𝐩𝐚𝐫𝐭: ✓ Full-stack AI delivery: requirements → architecture → deployment → maintenance ✓ Battle-tested across 50+ international projects ✓ Focus on business impact, not just technical complexity ✓ Clear communication and rapid iteration cycles 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: Computer Vision & Image Processing: Object detection | Image classification | ANPR systems | Face recognition | Video analytics | Image segmentation | OCR | Real-time tracking Natural Language Processing & LLMs: Chatbot development | RAG systems | LLM fine-tuning | Text generation | Sentiment analysis | Document summarization | Named entity recognition | GPT/Claude integration Audio & Speech Technologies: Automatic speech recognition (ASR) | Text-to-speech (TTS) | Speaker identification | Audio classification | Voice cloning | Noise reduction 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤:Python | TensorFlow | PyTorch | Keras | Scikit-learn | Hugging Face | LangChain | OpenAI API | FastAPI | Flask | Docker | AWS | Azure 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡:I take full ownership — understanding your use case, recommending the right approach, building the solution, and ensuring it works reliably in production. You get working software, comprehensive documentation, and post-deployment support. 𝐈𝐝𝐞𝐚𝐥 𝐅𝐨𝐫: Custom AI model development and training ML pipeline design and automation API development and third-party integration Proof-of-concept to production scaling Legacy system modernization with AI Let's discuss how AI can create measurable value for your business. Message me with your project details, and I'll respond with relevant examples and a clear path forward.

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.

I am an AI/ML engineer with 3+ years building production machine-learning systems, backed by a research track record: two accepted peer-reviewed papers, a two-time Google Summer of Code contributor, and published GPU work. What I can build for you: • LLM & vision-language fine-tuning — QLoRA/PEFT, dataset creation, evaluation, deployment-ready inference. • Self-hosted & open-source LLM deployment — running models on your own GPU servers for privacy, control, and lower cost. • RAG systems & AI agents — retrieval grounded in your documents, data, and tools, with evaluation and monitoring so it stays reliable in production, not just in a demo. • GPU & scientific computing — CUDA/CuPy/JAX acceleration, profiling, and pipelines that process terabytes of data • Full-stack delivery — FastAPI backends, React/Electron front-ends, Docker/Kubernetes, so the model ships as a real product your team can run How I work: define the use case, build the smallest reliable version first, test the edge cases, document everything, and hand you code your team can maintain after the contract ends. Core stack: Python, PyTorch, Hugging Face, CUDA/CuPy, FastAPI, React, Docker, Kubernetes. I am Top Rated with 100% Job Success and I reply within a few hours. Tell me what you're trying to build and I will build it for you.

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.

Expert-Vetted and Top Rated Plus (Top 1% )🏆🏆🏆 I am a Machine Learning Engineer/Data Scientist with 5 years of experience. I am a business-minded data scientist with an entrepreneurial spirit. My experience is in hands-on product development and implementation of data-driven products in the Computer Vision and Natural Language Processing domain, using state of the art deep learning algorithms. I propose modern and dynamic solutions to my clients for their business goals, and guide them throughout the journey to minimize the cost and maximize the output. I have experience working in an international environment and leading cross-cultural teams, and the ability to communicate fluently and clearly with team members, customers, and stakeholders. I have worked on the development of multiple AI/ML systems, serving millions of users at scale. Two of the Products that I am a part of, have raised seed funding totaling $1 Million. I have also been specializing in general machine learning, including academic and industrial research collaboration. Over the past 5 years, I have worked as an AI consultant and advised multiple projects in Computer Vision from bachelors to post graduate, in an industrial capacity. I have around 10 research publications in International conferences and Journals. Artificial Intelligence skills: ⠀✓ Supervised/Unsupervised/Semi-Supervised Learning Implementations ⠀✓ Classical Computer Vision Algorithm ⠀✓ Natural Language Processing/Natural Language Understanding ⠀✓ Edge-AI: Edge-Device Optimization, Jetson Nano, Jetson Xavier, Arduino, Raspberry Pi, Neural Compute Stick. ⠀✓ Image Processing and Deep Learning ⠀✓ Fast Neural Networks ⠀✓ Artificial Neural Networks (including DNN, CNN, FCNN, RNN, LSTM, GAN, VAE, etc.) ⠀✓ ML/DL tools: Scikit-Learn, PyTorch, Tensorflow, OpenCV, SciPy, NumPy, OpenVino ⠀✓ Data Manipulation/Visualization Tools: NumPy, Pandas, Matplotlib, Seaborn, NetworkX Whether it is working on a big and exciting project, or tutoring students on their final-year projects, I believe communication, trust and respect always come first. My strong points are Creativity, Punctuality, Responsiveness and Accountability. So, get in touch with me if you have an exciting idea you want to discuss the feasibility of, or just want some guidance or consultation on your next endeavor, I'm just a text away.

👋 Hi, I’m Mohamed — a Top Rated🏆 Senior Software Engineer. 🚀 I help companies design, build, and deliver high-performance software systems — from computer vision and AI pipelines to real-time desktop applications and embedded platforms. 🧩 What I deliver: ✅ Industrial Computer Vision Systems 🔹Integration with industrial cameras (Basler, Luxonis, FLIR / Point Grey) 🔹High-accuracy inspection, measurement, and defect detection 🔹Optimized OpenCV pipelines in C++ and Python 🔹Hybrid pipelines combining deep learning with classical computer vision for robustness ✅ Deep Learning (ResNet, U-Net, YOLO, MediaPipe, ...) 🔹Custom dataset creation, labeling, and curation 🔹Inference optimization for CPU, GPU, and edge devices 🔹YOLO for real-time object detection, segmentation, OBB, and pose estimation 🔹YOLO fine-tuning and transfer learning for domain-specific data 🔹MediaPipe for pose estimation, hand tracking, face landmarks, and motion analysis ✅ Real-Time & Performance-Critical Software 🔹Low-latency C++ systems optimized for speed and memory 🔹Multithreading, SIMD, profiling, and algorithmic optimization 🔹GPU acceleration (CUDA) when justified 🔹Designed for long-running, production-grade operation under real-world constraints ✅ Embedded & Edge AI 🔹Vision and AI deployment on Raspberry Pi 🔹Sensor integration, control logic, and hardware-in-the-loop testing with ESP32, Arduino ✅ Full Project Ownership 🔹System architecture and technical leadership 🔹Desktop GUIs: Qt, MFC, OpenGL 🔹Clean handover, documentation, and maintainable codebases 👉 Let's discuss how I can bring your AI, computer vision, or embedded system project to life.