• Developed a fully functional product recommender system using the crewAI framework, integrating a chatbot with a NextJS front‑end andWebSocket protocol for agent interaction in Flask web framework• Spearheaded a project focused on fine‑tuning the Phi‑3 model for buying intention detection• Created a synthetic dataset of over 12K samples using GPT‑4o to enhance model training

• Initiated an internship as an ML Engineer, focusing on a Retrieval-Augmented Generation (RAG)-based project.• Developed a system that integrates OpenAI models to enhance user prompts with relevant data from a vector database, using similarity measurements between user-provided prompts and stored data.• In the second phase of the project, adapted the process for tabular data (CSV, Excel) commonly used in business settings, aiming to extract meaningful insights as requested by users.• Built a performance monitoring system utilizing the EFK stack (Elasticsearch, Fluentd, Kibana) for conducting batch testing with predefined prompts.• Monitored key performance indicators, including system response duration, accuracy, and mismatched responses, to ensure efficient system operation and perform both performance and functional testing.

• Developed several projects’ back‑ends using Django framework• Experienced in working with various database management systems (DBMS) such as MySQL and PostgreSQL• Configured Docker container and Nginx along with CI/CD pipelines for testing• Utilized Django REST Framework’s serialization, authentication, and permission classes to ensure secure and efficient API functionality.

Develop and maintain web applications using Django framework• Optimize database queries and implement caching mechanisms to enhance application performance• Technical Skills: Python, Django, Docker, Ubuntu Linux• Soft Skills: Teamwork, Time Management, Communication