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I am a Machine Learning Engineer with four years of experience working across deep learning research, large scale AI systems, and production model deployment. Over the years, I have worked extensively in medical imaging, computer vision, NLP, signal processing, and large language models, building systems that range from experimental research pipelines to deployed real world AI applications. My day to day work primarily involves Python, PyTorch, TensorFlow, Keras, HuggingFace Transformers, sentence transformers, scikit learn, OpenCV, Pandas, and NumPy. I enjoy working deeply on both the research and engineering sides of machine learning, especially problems that require understanding model behavior rather than simply applying existing architectures blindly. A large part of my background is research driven. I have authored multiple peer reviewed publications in indexed journals and IEEE conferences, including publications in Neurocomputing, Healthcare Analytics, Engineering Applications of Artificial Intelligence, Telematics and Informatics Reports, and other Elsevier and IEEE venues. My research has focused heavily on explainable AI, healthcare AI, and advanced deep learning systems. Some of my published work includes CARDxnosis, an explainable knowledge driven framework for ECG diagnosis and clinical report generation, an explainable AI system for trustworthy arrhythmia detection, a CNN RNN Attention hybrid architecture for automatic modulation classification, ensemble deep learning approaches for lung cancer detection from CT scans, and SRGAN based white blood cell image generation and classification pipelines. Alongside published work, I am currently involved in research on brain tumor segmentation, ADHD and ASD classification from brain connectome graphs, epileptic seizure prediction from EEG signals, and interpretable tabular learning using graph neural networks combined with Kolmogorov Arnold Networks. Beyond research, I have substantial hands on experience building and deploying production grade AI systems. One of my major recent projects was LaborBERT v4, a domain adaptive transformer fine tuning system processing hundreds of thousands of records through a large scale training pipeline. The project involved multiple experimental setups including contrastive learning, masked language model pretraining, temporal contrastive learning, cross attention based fusion, multi task training, and Matryoshka Representation Learning. I have also built hybrid embeddings plus LLM systems for taxonomy mapping using OpenAI embeddings alongside locally hosted LLaMA and Mistral models through Ollama. In addition, I have worked on deployed clinical AI systems and a portable on device diagnostic AI solution with embedded deep learning models for point of care inference, which gave me valuable experience in optimization, deployment constraints, inference design, and production reliability. My broader project portfolio includes vehicle detection using Mask R CNN, human activity recognition on the Kinetics 700 dataset, facial keypoint detection with MultiRes UNet, semantic segmentation pipeline redesign, Stable Diffusion based image editing workflows, toxic comment classification, RASA based conversational AI systems, and large scale scraping and automation pipelines using Playwright and Selenium. I have also worked with Flask and Django based deployment pipelines and cloud hosted ML systems. From an engineering perspective, I care strongly about clean and maintainable systems. I follow disciplined workflows involving modular code design, Git based version control, reproducible experimentation, structured evaluation, bootstrap validated metrics, and detailed documentation. I am also comfortable preparing scientific reports, research papers, and journal submissions using both LaTeX and Word. What ties all of this together is that I genuinely enjoy solving difficult technical problems, especially the kind that require balancing research depth with practical engineering constraints. I am most motivated by projects where thoughtful experimentation, careful system design, and real world usability matter equally.

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 possess a rare combination of four complementary skill sets: web development, web scraping, machine learning, and quantum computing, enabling me to bridge software engineering, data-driven solutions, and emerging computational technologies. - 6 years of experience in Python-based machine learning & quantum computing. I have earned IBM digital badges in Quantum Machine Learning and Basics of Quantum Information, along with a Microsoft badge in Quantum Computing Foundations, demonstrating my commitment to advancing my knowledge in quantum technologies and their applications. - 15 years in web development (PHP, JavaScript, HTML, CSS), including - 14 years in WordPress programming including performance optimization & server administration and 13 years in Magento & Shopify. - Proven ability to deliver high-ranking, SEO-friendly websites without additional SEO efforts. - Fluent in English. - Strong knowledge in mathematics, physics, machine learning, and quantum computing, with advanced interdisciplinary expertise in complex systems enabling precise decision-making, efficient problem-solving, high efficiency, and consistently reliable results. ///// Due to space limitations, I highlight only the most advanced and most essential skills across my broad expertise. ///// Wordpress / Woocommerce / Shopify / Magento: * As I work with highly complex fields such as machine learning and quantum computing, working with these CMS platforms has become relatively straightforward for me. * With over 13 years of experience on magento/shopify and 14 years on wordpress/woocommerce, I am confident in my ability to meet all your requirements. I am capable of handling all aspects of these CMS platforms. I have developed several highly complex WordPress/WooCommerce websites using Elementor, some of which required over a year to complete. Kindly review the "In Progress" section of my profile to view my ongoing projects. As I work with highly complex systems such as machine learning and quantum computing—which require rigorous mathematical reasoning, deep abstraction, and advanced problem-solving—CMS platforms have become straightforward for me due to the comparatively lower level of complexity and predictable architecture they involve. My experience and skills make me distinctive. Page speed optimization skill (Wordpress / Woocommerce / Shopify / Magento): With over 13 years of experience in WordPress programming and speed optimization, I can boost your site’s performance to achieve 100% scores, sub-1-second load times, and green Core Web Vitals for both mobile and desktop on Google PageSpeed Insights and GTMetrix. My optimization efforts will make your website load at the fastest possible speed, typically under one second. Additionally, I address Core Web Vitals issues, including Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS), as reported in Google Search Console. Website speed is influenced by both the web server and website content. As an advanced-level programmer with expertise in complex systems such as Magento and Python machine learning, I optimize both the website and the web server using my extensive knowledge. This advanced-level expertise is crucial for achieving the fastest possible load times for your website. On-site SEO & Security: Experienced in WordPress on-site SEO, improving rankings, traffic, and performance through keyword research, meta optimization, schema, internal linking, and speed optimization. Skilled with Yoast SEO, Rank Math, and custom solutions for complex sites. I also ensure strong security via server hardening, firewalls, malware protection, and secure authentication. I integrate SEO, performance, and security to achieve lasting gains in Core Web Vitals, rankings, and conversions. Machine Learning and Quantum Computing: Over the past six years, I have been deeply engaged in the fields of machine learning and quantum computing. My passion for mathematics and physics, however, began in childhood and has driven a lifelong pursuit of knowledge in these areas. This strong foundation has enabled me to develop advanced expertise in both machine learning and quantum computing. Decision-making and problem-solving sill: Decision-making is a critical yet often overlooked skill in website development, essential at every stage—from selecting CMS, themes, plugins, and servers to implementing efficient PHP, CSS, HTML, and JavaScript for optimal performance and SEO, as well as solving development challenges. With over 15 years of freelance experience, I have seen many poorly built websites caused by suboptimal decisions. Alongside my strong programming background, I am also advancing my knowledge in physics and mathematics, which enhance analytical thinking, problem-solving, and decision-making.

I am an End-to-End AI/ML Engineer & MLOps Expert with a Top-Rated status and 100% Job Success Score, uniquely complemented by extensive experience as a Technical Content Strategist and Writer. My background allows me to not only design, develop, and deploy cutting-edge AI solutions but also to translate highly complex technical concepts into clear, engaging, and actionable documentation for both developers and end-users. As an AI/ML Engineer, I specialize in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), crafting intelligent, NLP-powered AI agents and applications. My expertise extends to the entire MLOps lifecycle, ensuring scalable, production-ready systems from concept to continuous deployment and monitoring on platforms like AWS. I excel at engineering complex, multi-modal systems for production environments, leveraging my expertise in both RAG and Computer Vision: - RAG & Speed: Designed a high-speed RAG pipeline using Groq that delivers conversational AI responses with an average time-to-first-token of under 150ms (AI Customer Feedback Platform). - Computer Vision & Full-Stack Deployment: Built RescueVision, an end-to-end multi-modal platform that fuses a custom, production-grade YOLOv8n (85.3% Precision) Computer Vision model with a FEMA-grounded RAG Mission Assistant on a React/Flask microservices architecture. - Cost-Conscious MLOps: Engineered a zero-cost prediction infrastructure on the AWS Always Free Tier (Lambda, API Gateway, S3) for a full-stack ML application, demonstrating cost-conscious, scalable cloud architecture. My engineering foundation, including a BSc in Electrical and Electronics Engineering degree and hands-on experience deploying projects on cloud platforms, provides a unique advantage in Technical Writing. Unlike many technical writers, I've personally engineered and deployed systems involving LLMs, RAG pipelines, MLOps, Cloud (AWS), and APIs, enabling me to deeply understand underlying architectures and pain points from a developer's perspective. I craft crystal-clear API Documentation, Developer Portals, MLOps Playbooks, System Architecture Docs, User Guides, and Knowledge Base articles. I leverage a robust tech stack including Python, PyTorch, TensorFlow, LangChain, Ollama, Docker, and MLflow for engineering, and Docusaurus, Confluence, and Postman for documentation. My commitment to quality, efficiency, and on-deadline delivery, combined with fluent English (Duolingo English Test: 135/160), makes me an ideal partner for secure, high-performance AI development and precise technical communication. What types of content do I produce? - AI/ML/Cloud Documentation: API Documentation, Developer Portals, MLOps Playbooks, System Architecture Docs - User Guides & Tutorials - Knowledge Base Articles & How-to Guides - Technical Blog Posts & Articles What tools do I use? - AI/ML/MLOps: Python, PyTorch, TensorFlow, LangChain, Ollama, MLflow, Docker, Git, GitHub Actions, AWS (Lambda, ECS Fargate, S3, CodeBuild), Render - Technical Writing/Content: Docusaurus, Confluence, Postman, Markdown, Google Docs, Surfer SEO, Yoast SEO, WordPress (for publishing) Who do I work for? - Software & SaaS Companies - Artificial Intelligence (AI), Machine Learning (ML), & Deep Learning (DL) Platforms - Startups & Innovation Labs - Cloud-Native Solution Providers - Web Hosting & E-commerce Tech Companies What are the topics that I work on? - Large Language Models (LLMs) & RAG Systems - MLOps & CI/CD Pipelines - Natural Language Processing (NLP) & Generative AI - Computer Vision - Data Science & Data Engineering - Cloud Computing (AWS) & Serverless Architectures - APIs & Microservices - Software Development Methodologies - System Architecture & Infrastructure What are my top skills? - End-to-End AI/ML Engineering - Large Language Models (LLMs) - MLOps & CI/CD - Technical Writing - Python - Natural Language Processing (NLP) - Computer Vision - Docker - AWS

Hi there!! I am Abdullah; a generative AI expert, and prompt engineer. As an experienced AI Image and Video Creator and AI Prompt Engineer, I specialize in delivering cutting-edge solutions that transform creative visions into reality. My expertise lies in leveraging advanced AI technologies to produce high-quality visual content and crafting precise, effective prompts that drive optimal performance in AI systems. What I Offer: 📸 AI-Driven Image and Video Creation: - Generation of high-quality images and videos tailored to specific needs. - Creative and realistic visual content using state-of-the-art AI tools. - Custom animations and visual effects for diverse projects. 📝 Prompt Engineering: - Development of precise and effective prompts to optimize AI model outputs. - Tailored prompt creation for various applications, including chatbots, content generation, and automation. - Expertise in fine-tuning and optimizing prompts for maximum efficiency. 💻 Technical Expertise: - Proficient in using leading AI tools and platforms. - Experience with machine learning frameworks such as TensorFlow and PyTorch. - Skilled in programming languages including Python, ensuring seamless integration and customization. 🤝 Professional Collaboration: - Strong communication skills to understand and fulfill client requirements. - Commitment to delivering high-quality work on time and within budget. - Flexible and adaptive approach to meet the unique needs of each project. Why Choose Me: 🚀 Innovative Solutions: I bring a creative and technical edge to every project, ensuring unique and impactful results. 😊 Client-Centric Approach: I prioritize client satisfaction, working closely to understand and achieve their vision. ✅ Proven Track Record: With a history of successful projects and satisfied clients, I deliver reliable and high-quality results. Let's work together to bring your creative projects to life with the power of AI. Whether you need stunning visual content or precise AI prompts, I am here to help you achieve your goals. Feel free to reach out to discuss your project requirements and how we can collaborate for success.

As a versatile freelancer, I specialize in Audio & Video Production, Machine Learning & Django Development, and Digital Marketing. With expertise in video editing and sound design, I create high-quality multimedia content. In Python development, I focus on building machine learning models and Django applications to meet your technical needs. My digital marketing skills ensure your projects gain the right audience through data-driven strategies. Whether it's crafting engaging videos, developing intelligent applications, or driving targeted marketing campaigns, I offer reliable and creative solutions for your projects.