- Contributed to several AI/ML projects with a focus on 2 main products as the following: + Developed a generative design system using ML models (Decision Tree, Random Forest, XGBoost) that suggests stylish and trending banners for clients by predicting optimal combinations of element features (sizes, colors, positions, etc)+ Experimented with various ML models (LOF, CBLOF, HBOS, IF, MCD, PCA) for detecting anomalies in API traffic. Drafted a Proof of Concept (POC) to propose practical solutions to potential leads- Performed data collection, data pre-processing, and feature selection to prepare clean datasets for efficient model training. Experienced in working with various data formats (JSONs, PDFs, images, spreadsheets, etc)- Researched DL models (GANs) to explore potential integration that facilitates even high-fidelity banner generation- Communicated project progress through detailed reports and delivered engaging live demos to clients, showcasing developed AI solutions- Researched and leveraged AWS services (SageMaker, EC2, Lambda, etc) to accelerate the development and optimize the performance of AI models

- Monitored and analyzed network traffic for client websites to identify periods of high traffic volume and potential bottlenecks, and timely notify clients of potential performance issues through email reports - Researched Google Cloud Platform services to identify suitable solutions for client needs