● Open to Work

ABHAY RISHNA

AI Developer Intern
California, United States

About Me

AI/MLEngineer specializing in Generative AI, LLMs, Agentic AI, and RAG pipelines. Proficient in Python, LangChain, Hugging Face Transformers, QLoRA fine-tuning, FAISS vector search, and deploying ML models via FastAPI and Streamlit.

Skills & Technologies

PythonSQLPandasNumPyScikit-learnMatplotlibLangChainLangGraphAgenticAIMCPTransformersLarge Language Models (LLMs)NLPDockerStreamlitFastAPIPowerBIExcelJupyter NotebookGoogle ColabPostmanGitLinuxWeb ScrapingChrome Extension Developmentn8nPowerBI Job Simulation | ForageNesternship | Nestlé

Work Experience

AI Developer Intern

Business Optima
Jun 2025Sep 2025

Engineered real-time AI automation using Hugging Face Transformers, LangChain, and Agentic AI, reducing manual processing by 40%. Designed Power BI dashboards and automated NLP-based document intelligence pipelines, cutting internal effort by 35%.

Gen AI Intern

Steps AI
Oct 2025Nov 2025

Built GitHub and Salesforce AI agents with web scraping pipelines to construct an automated knowledge base. Implemented Long & Short-Term memory in LangGraph agentic workflows for persistent, context-aware agents. Developed a RAG pipeline for Coal-India enabling semantic document search using vector embeddings and FAISS.

Projects

Medical Chatbot

Engineered a RAG-based medical chatbot using Streamlit, LangChain, FAISS, and Groq LLM, enabling semantic querying of PDF-based medical documents with accurate context-aware responses.

LangChainTransformerFaissGroq API+2

PhishShield

Implemented a phishing detection system using Python and Scikit-learn, trained on 50,000+ URLs achieving 95% classification accuracy using advanced feature extraction techniques.

PythonScikit-learnJavaScriptChrome Web Store

Fine Tuning LLM

Fine-tuned the LLaMA2 7B Chat model using QLoRA on the mlabonne/guanaco-llama2-1k dataset, optimizing training with 4-bit NF4 quantization for efficient resource utilization.

TransformersLLaMA2QLoRA

Modern RAG Architecture for Document Insights

Built a scalable Retrieval-Augmented Generation (RAG) API using FastAPI, Celery, Redis, PostgreSQL, and ChromaDB, enabling asynchronous multi-document ingestion and efficient semantic search across large datasets.

DockerRedisPostgreSQL

Education

B.Tech

Electronic Engineering

Rajiv Gandhi Institute of Petroleum Technology2022 - 2026

Class 12 (CBSE)

Beena Public School2019 - 2021
ABHAY RISHNA - AI Developer Intern | HiringAnt