AI/ML Engineer with hands-on experience in Machine Learning, Deep Learning, Generative AI, and AI Agent development. Experienced in building predictive models, CNN-based image classifiers, Voice AI systems, and LLM-powered automation workflows using Python, Tensor Flow, Scikit-Learn, Lang Chain, and Ollama.
Strong foundation in data preprocessing, feature engineering, model evaluation, and intelligent automation. Passionate about applying AI to solve real-world business and communication challenges.
Kodbud
Remote
Developed machine learning models for loan approval, spam detection, and diabetes prediction. Improved model accuracy through feature engineering and hyperparameter optimization. Conducted EDA on datasets containing 25K+ records. Used SQL and Python for data extraction, preprocessing, and analysis.
VoltQ Energy Cleantech LLP
Remote
Contributed to the development of AI-powered marketplace solutions for energy and sustainability products. Worked on Voice AI workflows integrating Speech-to-Text and LLM-based conversational systems. Assisted in developing multilingual communication concepts for cross-border marketplace interactions.
Explored AI agent architectures using Lang Chain, Ollama, and open-source AI frameworks. Participated in product information extraction and automation workflows using structured AI outputs.
Bachelor of Technology
CGPA: 7.02
PUC
Tech: Python, MercurJS, Whisper, Ollama, LangChain, PostgreSQL
Developed a multilingual voice-enabled marketplace for connecting vendors and customers across different languages. Designed Speech-to-Text → Translation → LLM → Translation → Text-to-Speech workflow for real-time communication between buyers and sellers. Integrated Whisper-based speech recognition and LLM-powered conversational search capabilities.
Built AI-driven product discovery and marketplace assistance features. Explored support for English, Telugu, Russian, and other languages through AI translation pipelines. Contributed to marketplace development using MercurJS multi-vendor architecture.
Tech: Python, Tensorflow, Keras
Developed and trained a custom CNN with 5 convolutional layers and dropout regularization on the CIFAR-10 dataset, achieving 82.61% test accuracy and reducing overfitting by tuning learning rate and batch size. Deployed the model on Google Colab and visualized results using Matplotlib and Seaborn.
Skill Intern
Forage
Kodbud
Branch Coordinator
Organized tech fest “TechniVerse 2K24” as EEE Branch Coordinator, managing 80+ participants and event logistics.
Member
Contributed to Digital Literacy Club, teaching basic computer skills to 100+ students.