Oussama LOUATI

Participate in the full software development lifecycle for artificial intelligence based systems - Design and build reliable, scalable, deployable, reproducible, and versioned data pipeline for AI-driven systems. - Setting up production-grade containerized or serverless cloud-based applications using infrastructure-as-code - Drive automation and monitoring of containerized and serverless deployments for software components and machine learning algorithms using CI/CD Pipelines. - Designing and building scalable pipelines for deep learning model training, prediction and scientific computation in collaboration with the research team - Deploying, serving and maintaining data infrastructure and machine learning models in production On-Prem & In Cloud - Building web API s and integrating storage and data solutions for managing AI workloads

End-to-end machine learning toolkit for data science and predictive analytics projects - Data gathering from various sources and storing it in any of the supported sources (GCS, S3, SQL databases) - Quick overview and annotation of the imported datasets (Python, Speedml) - Fully Automatic data visualization module (Plotly) - Including various data cleaning and transformation techniques (Sklearn, NLP) - Fully Automatic feature extraction, selection and generation (AuteEncoders, Featuretools) - Fully Automatic model building, selection and hyper-parameters tuning library. (Optuna, Ray tune)

Designing and building a recruitment platform: (Web development, Node.JS, No-SQL MongoDB, JavaScript, Trello) - Designed the different software architecture documents for the application. (UML diagrams) - Participated in meetings for architectural decisions of the application. (Agile Scrum sprints)