Hire the Best Computer Vision Engineers
in Bangladesh

With a strong background in machine learning, computer vision, and natural language processing, I have consistently delivered real-world AI solutions across diverse industries. My professional journey spans multiple roles where I have developed and deployed intelligent systems for image and language understanding, focusing on accuracy, performance, and scalability. Currently working as a freelancer, I have built intelligent data extraction pipelines for financial applications by combining advanced computer vision and NLP methods to extract information from bank cheques with high precision. Additionally, I worked on a complex chatbot project addressing the limitations of large language models (LLMs), such as context window constraints. I implemented optimization strategies like history truncation, prompt summarization, and prompt caching, which significantly improved coherence, processing speed, and memory efficiency in generated responses. As a Data Science Fellow at Fellowship.AI, I developed a robust evaluation pipeline to measure confidence levels in LLM outputs using datasets like LiveBench and MMLU. I applied strong evaluation metrics such as Expected Calibration Error (ECE) and BERTScore and utilized stronger LLMs for benchmarking, providing valuable insights into model calibration and reliability. Previously, as a Computer Vision Engineer at Hello Llama, I played a pivotal role in building IoT-enabled safety solutions. I developed end-to-end ML pipelines and Android applications integrating BLE and real-time video streaming, designed to work with radar warnings and dashcam systems. My work focused on real-time object detection of urban infrastructure and safety violations, deploying models on NVIDIA Jetson Nano for low-latency, edge-based inference. I also created a custom helmet detection system with facial focus and chin-strap detection and used sensor mat data to recognize multiple riders on scooters. My responsibilities included complete development cycles—from data collection to annotation, model training, validation on unseen data, and deployment—with comprehensive testing to ensure robustness in production environments. Earlier in my career as a Machine Learning Engineer at Expert Consortium Ltd., I worked on automatic face recognition and liveness detection systems. I designed pipelines capable of distinguishing live individuals from photographs and automatically created datasets for unknown individuals by organizing webcam feeds, labeling them, and training recognition models using LBP. I also built a driver activity recognition system for behavioral monitoring and an object tracking tool that captured snapshots when specific spatial triggers were activated. I utilized GPU acceleration and RabbitMQ to ensure high performance and seamless message passing during training and inference. Throughout my experience, I have demonstrated a unique ability to bridge the gap between computer vision and natural language processing. I have built robust pipelines, optimized LLM performance, engineered edge-deployable vision systems, and created intelligent, real-time applications in safety, finance, and mobility. My strengths lie in developing production-ready ML systems, optimizing performance in resource-constrained environments, and delivering intelligent solutions that scale effectively and meet real-world demands. I have direct Experience working on following topics: C++ Python Scikit-learn Tensorflow Keras OpenCv Embedded device Aws Azure Flutter

I'm a Senior Computer Vision Engineer with 7+ years of professional experience delivering enterprise-grade Computer Vision, Edge AI, Deep Learning & Machine Learning Solutions. I have a solid foundation in state-of-the-art deep learning models and machine learning algorithms, applying them to build, deploy, and optimize production-ready systems across edge devices, cloud platforms, and agentic AI pipelines. ✅ What I Build ▸ Computer Vision: object detection, tracking, segmentation, pose estimation, image classification, counting, OCR, anomaly detection ▸ Edge AI: NVIDIA Jetson (Nano, Orin, Xavier), Raspberry Pi, model optimization with TensorRT, ONNX, and TFLite for real-time inference ▸ Image Generation: Stable Diffusion (SDXL, SD 3.5), Flux, DALL·E 3, ControlNet, LoRA fine-tuning, ComfyUI workflows ▸ Video Generation: Kling, Runway Gen-3, Minimax Hailuo, Veo, Pika, automated cinematic and product video pipelines ▸ AI Agents: autonomous multi-step agents using LangChain, LangGraph, CrewAI, and AutoGen with RAG, memory, and tool use ▸ Voice AI: conversational voice agents using Vapi, Retell AI, ElevenLabs, Bland AI, and Deepgram for inbound/outbound calling and automation ▸ MCP Servers: custom Model Context Protocol servers connecting Claude and other agents to your APIs, databases, and internal tools ▸ Claude Code: agentic software engineering with subagent architectures, skill-based pipelines, and autonomous multi-step coding workflows ✅ Tech Stack ▪ Computer Vision: OpenCV, YOLO, MediaPipe, Detectron2, SAM, Vision Transformers ▪ Deep Learning: PyTorch, TensorFlow, Keras, ONNX ▪ Tracking & Optimization: DeepSORT, ByteTrack, TensorRT, OpenVINO ▪ Deployment: DeepStream, Triton Inference Server, TFLite, FastAPI, Flask, Docker ▪ Generative AI: Stable Diffusion, Flux, ComfyUI, Replicate, Fal.ai ▪ Agents & Voice: LangChain, LangGraph, CrewAI, Vapi, Retell AI, ElevenLabs, n8n ▪ MCP & Agentic: Claude Code, MCP SDK, custom tool servers ▪ Cloud: AWS, GCP, Azure ▪ Languages: Python, C++, CUDA 🚀 Send me a message with what you are trying to build, and let's discuss.

🚀 Robotics & Computer Vision Engineer | ROS2 | Embedded Systems I design and build intelligent robotic systems that bridge software, hardware, and perception. My expertise spans Robotics, Computer Vision, Stereo Vision, SLAM, and Embedded Systems, with a strong focus on real-world, deployable solutions. Core Skills & Expertise: Robotics development with ROS & ROS2 Stereo vision, depth estimation, and visual SLAM Computer vision using OpenCV Vision-based localization and navigation Embedded systems & IoT integration Tech Stack: C, C++, Python Isaac Sim, Gazebo & RViz for simulation and visualization Arduino, ESP32, STM32, Raspberry Pi, Radxa, Orange Pi Solidworks, Fusion 360 for custom robotic and mechanical design I work comfortably across the entire robotics stack—from perception and planning to control and hardware integration—delivering efficient, scalable, and cost-effective systems. If you need a reliable engineer to turn complex robotics ideas into working, high-performance solutions, let’s talk.

I am an expert AI/ML Engineer with hands-on expertise in Machine learning, Deep Learning, Computer Vision, NLP, Generative AI, and LLMs. I leverage advanced techniques to deliver innovative and impactful AI solutions for your needs. Areas of expertise: ✅ Machine Learning (Data Analysis and Visualization, Classification, Regression models, Predicting with Supervised, Unsupervised Techniques) ✅ Deep Learning (Deep Neural Networks, Transfer Learning, fine-tuning models, XAI, optimization, exploring models) ✅ Computer Vision and Image Processing (Object detection/segmentation/tracking, Image/Video classification, Image generation, OCR) ✅ NLP (Text classification, Topic modeling, NER, Semantic similarity, Text generation, Question Answering) ✅ Generative AI (Fine-tuning LLMs, RAG, Prompt Engineering, embeddings, vector database, Chatbots and AI Assistants) ✅ Audio Data Analysis (Audio classification, Sound segmentation, TTS, STT) Tech Stack: ✅ ML/DL tools: TensorFlow, Keras, PyTorch, Scikit-Learn, XGBoost, LightGBM, CatBoost ✅ NLP: LangChain, OpenAI(GPT-4, Embeddings, ChatGPT), Local LLMs, Huggingface, Gemini, NLTK, Textblob ✅ Computer Vision: Ultralytics, OpenCV, Pillow, Scikit Image, YOLO, Detectron2, OpenPose ✅ Data Analysis/Visualization Tools: Pandas, NumPy, Matplotlib, Seaborn, Plotly, Altair ✅ Cloud services: AWS, Google Cloud, Azure ✅ Project Management and Version Control: Git, GitHub ✅ MLOps: MLFlow, Docker, Github actions, Airflow, DVC ✅ Deployment: StreamLit, Flask, FastAPI ✅ Languages: Python My commitment to excellence and continuous learning ensures that I stay at the forefront of AI/ML advancements. Let’s connect to explore how I can contribute to your AI/ML projects and help you achieve your business goals with cutting-edge solutions.

⭐⭐⭐⭐⭐ Turn your ideas into viable AI apps and services. ✅ Computer vision ✅ Deep Learning ✅ Image Processing ✅ Machine Learning ✅ Generative AI ✅ Web Scraping ✅ Data Analysis 🚀 Whether you're launching a new computer vision or machine learning project or enhancing an established one, I aim to provide solutions that perfectly align with your objectives. As an experienced machine learning and computer vision engineer, I make the connection between high academic standards and real-world use. My M.Tech experience, which is based on modern artificial intelligence principles, enables me to transform both cutting-edge research and tried-and-true machine learning and deep learning models into solutions that are specifically suited for your challenges. Check out my offered services: 💢 Computer Vision: Deep Learning, Image Classification, Object Detection, Object Tracking, Pose Detection, Image Segmentation, and Image Processing Focusing on: ☑️ Live Object Detection with Webcam ☑️ Face and person re-identification (ReID) ☑️ Image Processing | Edge detection ☑️ Single/Multiple Object Tracking CCTV ☑️ Single/Multiple Image Classification ☑️ Pose Estimation | KeyPoint Detection ☑️ Action Recognition ☑️ Python GUI development ☑️ Image segmentation (semantic and instance) ☑️ OCR Image to Text 💢 Machine Learning: Data Analytics, Data Science, Predictive Analytics, Recommendation Systems, Anomaly Detection, Healthcare, Finance, Marketing, and Sales Focusing on: ☑️ Web Scraping ☑️ Data Analysis and Visualization ☑️ Feature engineering ☑️ Predictive Modeling ☑️ Recommendation Systems ☑️ Anomaly Detection ☑️ Time Series Forecasting ☑️ Model Deployment and Integration ☑️ Custom Machine Learning Solutions 💢 Notable Project Expertise Computer Vision, Image Classification, Object Detection, Image Segmentation, Pose Detecton, Medical Data Analysis, Face Detection, Video Analysis, Machine Learning and Other Deep Learning Projects ☑️ Object Detection using YOLO-NAS/ YOLOv8/ YOLOv7 ☑️ Object Detection and Tracking using YOLO-NAS / YOLOv8 / YOLOv7 and SORT/ DeepSORT / Bytetrack ☑️ Object Segmentation using YOLOv8 ☑️ Object Detection and Segmentation using YOLO-NAS and Segment Anything Model ☑️ YOLOv8 Segmentation with Multiple Object Tracking ☑️ Grocery Items Detection in a Retail Store with YOLO-NAS / YOLOv8 / YOLOv7 ☑️ Personal Protective Equipment Detection using YOLO-NAS / YOLOv8 / YOLOv7 ☑️ Vehicle Analytics with YOLO-NAS / YOLOv8 / YOLOv7 ☑️ African Wildlife Animals Detection and Tracking Using YOLO-NAS / YOLOv8 / YOLOv7 and Bytetrack/ DeepSORT/ SORT. ☑️ Personal-Protective-Equipment Detection Using Deep Learning and Python (YOLOv7) ☑️ Underwater (Fish and its types) Detection Using YOLO-NAS /YOLOv8 / YOLOv7 ☑️ AI Personal Trainer (Pushup, Biceps & Crunch Counting) Using MediaPipe. ☑️ Automatic Number Plate Recognition using YOLO-NAS/YOLOv8/YOLOv7 and Tesseract OCR / Paddle OCR / EasyOCR ( Images & Videos) ☑️ Fish Eye Camera People Detection and Object Tracking Using Machine Learning ☑️ Heatmap generation Using EigenCam and Object Detection (YOLOv8, YOLOv5) ☑️ Object Detection Using Transformers (RT-DETR) ☑️ Tennis Shots Identification and Counting using YOLOv7 Pose Estimation and LSTM Model ☑️ Vehicle Intensity Heatmaps using YOLO-NAS / YOLOv8 / YOLOv7 ☑️ Real Time Sign Language Detection with YOLO-NAS/ YOLOv8 / YOLOv7 and Webcam ☑️ Plastic Bottles Counting on Manufacturing Lines with YOLO-NAS / YOLOv8 / YOLOv7 and Object Tracking using SORT / DeepSORT / ByteTrack ☑️ People Face Detection, Segmentation, and Blurring Using YOLOv8 ☑️ Fruits Detection on Custom Dataset Using YOLO-NAS / YOLOv8 / YOLOv7 ☑️ Football Player Detection and Tracking Using YOLO-NAS / YOLOv8 and SORT / DeepSORT / ByteTrack ☑️ Multiple streams of object tracking and object detection. ☑️ Traffic Lights Detection and Color Recognition using YOLO-NAS / YOLOv8 ☑️ People Counter using YOLOv8 and Object Tracking using SORT/ DeepSORT/ Bytetrack ☑️ Potholes Detection using YOLOv8 (Images & Videos) ☑️ Potholes Detection and Segmentation using YOLOv8 (Images & Videos) ☑️ Fire and Smoke Detection using YOLO-NAS/ YOLOv8/ YOLOv7 ☑️ Waste Detection using YOLO-NAS / YOLOv8 / YOLOv7 ☑️ Waste Detection and Segmentation using YOLOv8 ☑️ Traffic Watch: Automated Vehicle Direction Detection and Counting using YOLOv8 ☑️ Face Detection, Gender Classification, Counting, Tracking, Alert and Analytics ☑️ Helmet Detection and Segmentation using YOLOv8 ☑️ Cracks Segmentation using YOLOv8. ☑️ Car Velocity Calculation + Vehicles Counting (Entering and Leaving) ☑️ Web App: Vehicles Counting using YOLO-NAS/YOLOv8/YOLOv7 and SORT/DeepSORT/Bytetrack Object Tracking ☑️ Streamlit App to Count the Vehicles Entering and Leaving 💬 Send me a message so we can discuss your projects! 😊 Looking forward to working with you!

I am an experienced Machine Learning Engineer with a strong background in developing state-of-the-art AI systems. Over the years, I have contributed to impactful projects such as Bangla ASR, TTS, and OCR systems, as well as large-scale language models. I have hands-on experience integrating advanced AI technologies like Large Language Models (LLMs), ASR, and TTS into real-world applications. Highlights of my expertise: -Google Summer of Code 2023 participant for OpenVINO Toolkit by Intel. -Extensive work in AI research and development, including projects on historical watermark recognition and human pose estimation. -Skilled in Python, Machine Learning, Deep Learning, and integrating AI models for scalable solutions. -Adept at designing solutions for speech recognition, image processing, and workflow automation with AI tools. I am passionate about solving complex industry problems through cutting-edge AI solutions, ensuring scalability, efficiency, and reliability.