Driving data-driven solutions for businesses by transforming complex data into actionable insights. Specializing in developing and implementing machine learning solutions while leading technical innovations in our data analytics pipeline.Key Responsibilities:* Design and implement end-to-end data solutions from collection to visualization* Develop machine learning and NLP models to automate and enhance data analysis* Create AI-powered applications to improve data accessibility and business intelligence* Lead data visualization initiatives to communicate insights effectively* Manage and optimize data infrastructure using cloud-based technologiesTechnical Focus: Machine Learning, Natural Language Processing, Data Analytics, Business Intelligence, Cloud Computing

As a Machine Learning Engineer, I lead initiatives to enhance user experience and engagement through innovative technology and strategic collaboration. Highlights of my role include:* Developing a dynamic search engine using Large Language Models (LLMs), significantly improving relevance.* Engineering algorithms to optimize search result ranking, boosting user engagement.* Orchestrating large-scale web scraping for data acquisition and model training.* Fine-tuning LLMs for efficient processing of datasets.* Building machine learning models for product categorization, enhancing search accuracy.* Collaborating cross-functionally to align improvements with user needs.* Conducting rigorous testing to ensure performance and scalability.* Contributing to technical strategy for enhancing search capabilities.

* Developed and implemented a text scoring system using deep learning techniques to optimize evaluation processes.* Collaborated with clients to define system requirements and ensure alignment with their objectives.* Designed and deployed a specialized system for marine creature detection, contributing to research efforts.* Provided guidance and instruction to master's students on system design principles and advanced computer vision techniques.

* Assisted in hardware design of Next Generation Smart-Grid Meter (NSGM).* Developed C++ script for efficient data collection and transmission to cloud.* Implemented PyTorch-based deep learning model for power consumption forecasting.* Utilized variational autoencoder for non-intrusive load monitoring.* Designed algorithm for harmonics and anomaly detection, enhancing grid stability.

* Developed Arabic Automatic Speech Recognition (ASR) prototype.* Designed Transformer-based encoder-decoder architecture.* Achieved 12% Word Error Rate (WER) on Mozilla Common Voice dataset.* Utilized Google Cloud Platform (GCP) with GPU for efficient model training.* Collaborated with development team for chatbot integration.

* Developed AI-based module to detect cheating in online lab exams using mouse interaction analysis.* Employed KNN, SVC, Random Forest, Logistic Regression, XGBoost, and LightGBM algorithms for classification.* Conducted experiments validating effectiveness of approach with up to 90% accuracy using LightGBM.* Achieved 88% precision and 95% degree of separation in cheat detection.