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Karthik Hugar

Generative AI Engineer • Bengaluru, India • k***************@gmail.com • drivetube.ai/•••••

Professional Summary

Generative AI Engineer with 0 years of experience building RAG pipelines, LLM-backed APIs, and production AI endpoints. Skilled in Python-based backend development (Flask, FastAPI) and embedding-based retrieval using ChromaDB and FAISS to enable context-aware applications. Experienced with LangChain orchestration, prompt engineering, and model inference via Groq API and Gemini Pro for recommendation and resume-analysis systems. Built semantic search, embedding pipelines, and production-ready endpoints integrated with MySQL-backed storage and Streamlit dashboards. Published researcher in attention-enhanced LSTM and XGBoost forecasting, demonstrating strong ML modeling and evaluation capabilities. Comfortable owning end-to-end ML features from data processing and embeddings to API deployment and developer documentation.

Technical Skills

Programming Language: Python
Backend Technologies: Flask,FastAPI
Databases: MySQL
Version Control & Development Tools: Git,GitHub
Data Analysis & Visualization: Streamlit,Data Structures and Algorithms
Machine Learning & AI: Natural Language Processing
AI/ML Frameworks & Libraries: scikit-learn
Generative AI & LLMs: LangChain,Gemini Pro,Groq
Vector Databases & RAG: Retrieval-Augmented Generation,ChromaDB,FAISS

Work Experience

Edufu Technologies (CampusPe)
Bengaluru, India
Generative AI Intern
Feb 2026 – May 2026
Worked at Edufu Technologies (CampusPe), an education-focused platform; supported AI backend services that delivered recommendation, reporting, and conversational RAG functionality.
Tech Stack: Flask, ChromaDB, LangChain, Retrieval-Augmented Generation
  • Built Flask-based AI endpoints to expose recommendation and report-generation features, connecting client requests to LLM inference backends via Groq API.
  • Implemented retrieval-augmented generation pipelines that combined ChromaDB vector stores with sentence-transformer embeddings to provide context-aware responses.
  • Developed LangChain orchestration and standardized prompt templates to improve prompt reliability and reduce variation across generation tasks.
  • Integrated recommendation and reporting endpoints with application backends by defining REST schemas, request validation, and robust error handling in Flask.
  • Optimized semantic retrieval by adjusting embedding chunking and index configuration to improve relevance for conversation-driven queries.
  • Authored integration guides and API usage documentation to onboard product and backend teams for AI endpoint consumption.

Projects

Kapture Finance – AI Voice Collection Agent
Tools Used: Python, FastAPI, MySQL, Streamlit, Git, GitHub
  • Built an end-to-end AI voice collection agent to automate customer payment follow-up and debt collection conversations using a FastAPI webhook backend.
  • Integrated Vapi with FastAPI to perform customer identity verification, account information retrieval, and automated collection workflows.
  • Implemented MySQL persistent storage for customer accounts, call history, Promise-to-Pay commitments, and call dispositions to maintain auditability.
  • Developed branching collection workflows to handle outcomes including PTP agreed, already-paid, hardship escalated, no-response, and authentication failures.
  • Designed an interactive Streamlit analytics dashboard to visualize collection metrics, call history, payment commitments, customer portfolios, and risk distribution.
Crop Recommendation System
Tools Used: Python, scikit-learn, OpenWeatherMap API, NASA POWER API, gTTS, Streamlit
  • Trained a Random Forest classifier on soil and climate features to provide crop recommendations tailored to local conditions.
  • Integrated OpenWeatherMap and NASA POWER APIs to enrich feature sets with real-time and historical climate data for model inputs.
  • Implemented bilingual voice assistance using gTTS to improve accessibility for regional-language users.
  • Deployed a Streamlit interface supporting Kannada and English inputs to broaden usability across user groups.
  • Achieved approximately 92% classification accuracy on validation data through feature engineering and hyperparameter tuning.
AI-Powered ATS Resume Analyzer
Tools Used: Python, Gemini Pro, FAISS, MySQL, Streamlit, Git, GitHub
  • Built an AI-powered ATS that performs resume-to-job-description semantic matching using Gemini Pro for embedding and inference.
  • Implemented embedding-based retrieval with FAISS for similarity scoring across chunked resume content to surface best-fit candidates.
  • Developed keyword-gap analysis and candidate ranking features and visualized results via an interactive Streamlit dashboard.
  • Integrated MySQL to persist candidate feedback and historical evaluation results for audit and trend analysis.
  • Designed resume chunking, embedding workflows, and similarity thresholds to balance recall and precision in candidate matching.

Education

CMR Institute of Technology
Bachelor of Engineering in Computer Science and Engineering • Bengaluru, India • 2022 – 2026

Certifications

Oracle Cloud Infrastructure 2024 Generative AI Certified Professional — Oracle
AWS Certificate (Udemy) — Udemy
Python Data Structures and Algorithms — Udemy
MySQL – NxtWave CCBP 4.0 Intensive — NxtWave

Achievements

  • LeetCode 50-Day and 100-Day Streak Badges: Demonstrated consistent daily practice in Data Structures and Algorithms through multi-month coding streaks.
  • ICCIDS 2026 Publication — 2026: Published 'Attention-Enhanced LSTM and XGBoost for Agricultural Market Price Forecasting' presenting a hybrid model that outperformed baseline LSTM.

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