Pushing the boundaries of Artificial Intelligence
AI Engineer with comprehensive experience in Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision. Demonstrated expertise in developing intelligent systems with published research.
Passionate about leveraging AI to solve complex problems at scale, with strong technical foundation in Python, TensorFlow, PyTorch, and data analysis. Seeking to apply research experience and technical skills to develop innovative AI solutions.
More about meResearch Interests
Natural Language Processing
Multilingual models, tokenization optimization, and efficient language understanding
Computer Vision
Object detection, image segmentation, and multimodal vision-language models
Reinforcement Learning
Strategic decision making, game AI, and multi-agent systems
Academic Background
Foundation in Artificial Intelligence and computer science
University at Buffalo, State University of New York
Master of Science in Engineering Science
Artificial Intelligence
Kakatiya Institute of Technology and Science, Warangal
Bachelor of Technology
Computer Science
Featured Work
Innovative AI solutions I've developed
LLM RedHat Toolkit
Enterprise-Grade LLM Deployment Platform
Built an LLM-based interactive platform integrating LangChain with enterprise data sources and custom RAG pipelines. Deployed LLM inference with Streamlit UI and Docker containers for scalable and modular access to fine-tuned models.
Intelli-Chat
AI-Powered Conversational System
Architected scalable chatbot system processing 60,000+ documents with hybrid retrieval-augmented generation approach.
Tokenization Challenges in Multilingual GPT
NLP Research & Implementation
Researched and implemented optimized tokenization for multilingual language models, improving efficiency by 60% for non-English languages.
Multi-Language Translation System
Neural Machine Translation
Built production-ready neural translation system supporting 5+ language pairs with 85% BLEU score using sequence-to-sequence architecture.
Meme Persuasion Detection
Multimodal Content Analysis
Developed multimodal classification system for detecting persuasion techniques in internet memes with 78% accuracy using BERT and ResNet-50.
Professional Journey
My experience in AI research and development
Software Engineer I
Arrant TechApr 2025 - Present
Lead AI Application Developer for LifeConnectApp, an autonomous AI agent system that monitors and automates social media interactions across multiple platforms. Building enterprise integrations using Workday Extend and developing secure authentication systems.
Key Achievements
- Lead AI Application Developer for LifeConnectApp, an autonomous AI agent system that monitors and automates social media interactions across multiple platforms (Google, LinkedIn, Facebook, Instagram)
- Architected core AI system components including GPT-4-powered NLP, real-time monitoring modules, and automated response generation capabilities
- Building enterprise integrations using Workday Extend to streamline business workflows and enhance system interoperability
- Built secure authentication systems with JWT and OAuth 2.0, ensuring data privacy and encrypted storage solutions with MongoDB
- Developing Virtual Clean Rooms (VCR) Management System, a full-stack web application (Python + JavaScript)
- Building ArrantMeet, an internal Workday Extend-based meeting management and scheduling application
Artificial Intelligence Prompt Engineer
Community Dreams FoundationFeb 2025 - Present
Volunteer contributor developing and refining AI prompts for ML-driven simulations, improving model reliability and collaborating on architecture optimization.
Key Achievements
- Volunteer contributor developing and refining 100+ AI prompts for ML-driven simulations, improving model reliability by 30%
- Collaborate on architecture optimization discussions to enhance platform scalability and performance
Artificial Intelligence Research Intern
Kakatiya Institute of Technology and ScienceFeb 2023 – Jun 2023
Optimized tokenization in multilingual language models, improving efficiency by 60% for non-English languages. Developed language-specific preprocessing pipelines, reducing token usage per prompt from 70-100 to 18-25.
Key Achievements
- Published research paper 'Tokenization Challenges in Multilingual GPT' at ICIIRS-23 conference
- Reduced token usage by 75% for non-English languages
- Enhanced response speed using transliteration-based preprocessing
- Implemented preprocessing pipeline used by 200+ students
Machine Learning Research Intern
Kakatiya Institute of Technology and ScienceMar 2023 – Jul 2023
Engineered ML pipeline for fraud detection achieving 78% accuracy and 81% AUC using ensemble methods. Implemented data balancing and feature engineering techniques to optimize model performance on imbalanced datasets.
Key Achievements
- Published research paper 'Fraud Detection in Automobile Insurance Claims using Machine Learning Algorithms' at ICIIRS-23
- Developed ML models (RF, KNN, DT, SVM) for fraud detection, selecting Random Forest as optimal
- Conducted extensive evaluation despite data imbalance, demonstrating RF's superior performance
- Created reusable feature engineering pipeline for insurance data
Technical Expertise
Core competencies and technologies