● Lead the development and deployment of AI models, focusing on improving accuracy, efficiency, and scalability. ● Refine, and optimize prompts for large language models (LLMs) to improve their Performance in specific tasks. ● Designed PoCs to validate AI-driven solutions for real-world applications. Projects: 1. AI-Powered Exit Interview System (Jan 2025 – Feb 2025): ● Developed a real-time AI-driven exit interview system using NLP and generative AI to analyse sentiment and provide insights. ● Integrated GPT-based AI models for structured conversational analysis and optimized model inference time, reducing processing latency by 30%. ● Technologies: Python, Deepgram API, OpenAI GPT, Streamlit. Market Research Analysis System (Dec 2024): ● Developed an AI-driven application that automates the market research process and generates detailed reports for companies. ● Developed CrewAI framework and Leveraged Gemini LLM for advanced language processing and SerperDev API for enhanced search functionality. ● Built an interactive user interface with Streamlit for easy user engagement and input.

● Contributed to project planning and task estimation to ensure timely delivery of features. ● Engaged in continuous learning and development, staying updated with the latest trends and technologies in python development. Projects: 1. Object Detection and Voice Assistance for Visually Impaired Person. (July 2024 – Nov 2024) ● Developed a real-time object detection system with voice feedback for visually impaired users, utilizing YOLO and OpenCV. ● Integrated IoT-enabled sensors and devices for continuous environmental monitoring feedback and timely auditory alerts. ● Utilized Python, TensorFlow, and Raspberry Pi for robust system design and deployment. 2. Fake News Classification Using Deep Learning (Jan 2024-Feb 2024) ● Developed a deep learning model to classify news articles as reliable or unreliable, addressing the Challenge of fake news detection. ● Technologies Used: Python, TensorFlow, Kera’s, Scikit-learn, Glove, Flask, NLTK, Pandas, NumPy. ● Built and compared sequence models (RNN, LSTM, GRU) to evaluate performance and efficiency. ● Improved detection efficiency, reducing the spread of misinformation through automated classification.

● Collaborated with the data science team to analyze and interpret complex data sets to drive decision-making processes. ● Developed and implemented machine learning models to predict key business metrics, improving accuracy and to conducted exploratory data analysis (EDA).

● Team up to analyze large datasets using big data technologies to extract meaningful insights and trends utilized tools such as Hadoop, Spark, Machine Learning. ● Implemented data visualization techniques using tools like Tableau, Power BI, and Matplotlib to present findings to stakeholders. ● Assisted in the design and development of data pipelines and ETL processes to automate data workflows.