ARTIFICIAL INTELLIGENCE DEVELOPER

• Developed LLM-based chatbot using RAG, semantic search, and document QA pipelines
• Built end-to-end Generative AI pipelines with LangChain, LangGraph, OpenAI embeddings, and ChromaDB
• Designed document ingestion, chunking, vectorization, vector database, similarity search and retrieval pipelines for unstructured PDFs
• Applied prompt engineering, evaluation, and hallucination reduction techniques for LLM reliability
• Developed scalable AI systems with Streamlit frontend, REST APIs, and FastAPI, following AIOps

RESEARCH ASSISTANT IN REINFORCEMENT LEARNING FOR MICROROBOT CONTROL

• Built RL environment using MuJoCo and Gymnasium for microrobot navigation
• Simulated magnetic coil system, Field Free Point (FFP) control, and maze environments
• Applied reinforcement learning algorithms for autonomous navigation using RL agent
• Evaluated MuJoCo, PyBullet, Gazebo, and Blender for simulation optimization
• Managed experiments using Git, Docker, and virtual machines (VM) for reproducibility and scalability

WORKING STUDENT R&D CLOUD OPERATIONS (AI Specialist)

Projects: GenAI / NLP / LLM Systems

• Engineered and fine-tuned transformer models (BERT) and built applications using GPT-based LLMs, used Qdrant vector database
• Applied advanced NLP methodologies to generate customer responses, reducing response time by 25%
• Executed data preprocessing, including tokenization, text normalization, and feature extraction

Projects: Data Engineering / AI Automation / Cloud

• Developed an AI-driven automated customer reporting tool using Python, integrating REST APIs
• Implemented CI/CD pipelines for preprocessing and ingestion, reducing failures by 11%
• Developed an AI tool for automated data migration, using data analysis and preprocessing
• Integrated CI/CD pipelines for cloud migrations across AWS, Azure, lowering release lead time by 25%
• Automated data processing workflows, ensuring efficient migration and maintaining data integrity
• Automated image scraping and color classification (Selenium, Beautiful Soup, OpenCV) for enhanced decision-making, improved classification accuracy to 15%

INTERN DATA ANALYTICS AND MACHINE LEARNING DEVELOPER

• Responsible for developing ML models for automated statistics generation of various databases, enhancing reporting efficiency by 40%, following MLOps practices
• Applied MA, ARIMA, and LSTM models for time-series forecasting, code optimization of ML models
• Built preprocessing modules, optimized and boosting scalable ETL/ML pipelines performance by 30%
• Optimized and maintained scalable ETL/ML pipelines using AWS Glue, S3, Athena, and QuickSight, EC2
• Created data visualization modules and Dashboards for complex dataset using python, plotly, Power BI

INTERN MACHINE LEARNING DEVELOPER

• Developed ML frameworks for two key automation projects, contributing to production-ready pipelines
• Implemented automation scripts in Python, reducing manual operation by 30% for processing workflows
• Leveraged mathematical aspects of AI (regularization, optimization, feature scaling) to improve AI model performance by 15% using mathematical expertise
• Applied K-Means clustering and Deep Learning for customer segmentation, improving targeted marketing effectiveness and increasing retention by 12%

INTERN DATA ANALYST

• Led database design, management for project, Ensured data quality and reliability through assessments
• Analyzed large datasets to identify trends and improve communication of valuable insights and KPIs
• Improved data flow process, achieving 25% faster data handling, Converting data into actionable insights