I am an entry-level Generative AI Developer, AI/ML Engineer, and Python Developer with a B.Sc. in Computer Science and Cognitive Systems and a completed Master AI Program.
I build Python-based Generative AI applications, including LLM integrations, Retrieval-Augmented Generation (RAG) workflows, chatbots, REST APIs, and full-stack web applications using FastAPI and React.
I have hands-on machine learning and deep learning experience with TensorFlow, Keras, and Scikit-learn. My work includes anomaly detection, text classification, computer vision, data preprocessing, and model evaluation.
During my Machine Learning Project Internship at VCODEZ, I developed an autoencoder-based fraud detection solution for identifying suspicious credit card transactions and delivered a Streamlit application for real-time prediction.
I have built AI products featuring Google Gemini, NVIDIA-hosted GLM models, Hugging Face image generation, streaming responses, PDF analysis, JWT authentication, and SQLite-backed applications.
I am seeking an entry-level opportunity in Generative AI, AI/ML engineering, or Python development where I can apply my practical development and machine learning skills.
Developed an autoencoder-based anomaly detection model using Python, TensorFlow, and Keras to identify potentially suspicious credit card transactions.
Worked with a highly imbalanced transaction dataset, applying data preprocessing and model evaluation techniques. Used reconstruction error and a threshold-based approach to flag potentially fraudulent transactions.
Built a Streamlit application for real-time fraud prediction and transaction-level analysis.
Master AI Program, Artificial Intelligence
Completed Master AI Program.
Bachelor of Science, Computer Science & Cognitive Systems
Completed B.Sc. in Computer Science & Cognitive Systems with a CGPA of 68.8%.
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