About Me
Results-driven AI Engineer experienced in developing and deploying end-to-end AI/ML models for NLP, Computer Vision, and Generative AI applications. Proficient in Python, TensorFlow, PyTorch, and cloud AI services. Stron…
Results-driven AI Engineer experienced in developing and deploying end-to-end AI/ML models for NLP, Computer Vision, and Generative AI applications. Proficient in Python, TensorFlow, PyTorch, and cloud AI services. Strong expertise in LLMs, chatbot development, and Retrieval-Augmented Generation (RAG). Adept at data pipeline design, prompt engineering, and AI integration into enterprise workflows. Seeking opportunities in Dubai or Saudi Arabia to contribute to cutting-edge AI innovation and digital transformation.
Experience
AI Engineer Intern
Developing and deploying machine learning models using Python
Working with data analysis and visualization tools to drive impactful insights across various domains
Mastered core Python concepts, including variables, data types, control structures, functions, and collections
Developed efficient algorithms leveraging loops, class objects, and operators
Created visualizations such as bar charts, scatter plots, and network graphs to translate complex data into actionable insights
Applied visualization techniques for financial analysis, healthcare, marketing, and HR
Skilled in data cleaning, handling missing values, outlier detection, and feature engineering to improve dataset quality
Developed supervised learning models, including linear and logistic regression, and classifiers like Naive Bayes, KNN, and SVM
Implemented unsupervised learning algorithms, including K-means clustering and PCA, to uncover hidden data patterns
Gained experience in CNN-based architectures such as YOLO V8 and RCNN for real-time object detection and image classification
Built AI/ML models for medical research, predicting patient conditions based on biomechanics features
Applied K-means clustering in the automotive domain to categorize vehicle types
Leveraged machine learning models to analyse and predict team performance in basketball tournaments and customer churn for telecom companies
Used Pandas and Numpy for data handling, Matplotlib and Seaborn for visualization, and Scikit-learn for model building
Performed model evaluation with accuracy, precision, recall, and F1-score
Improved performance through hyper parameter tuning and grid search
AI Engineer Intern
Developing and deploying machine learning models using Python, data analysis and visualization