KARTHIK ABHIRAM PIPPALLA

AI/ML · NLP · RAG · Backend Systems

Developing machine learning, NLP, RAG, and backend systems with Python, PyTorch, TensorFlow, FastAPI, and MongoDB — from model experimentation to production deployment.

Florida, USA
(754) 269-5640 · abhipippalla@gmail.com

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About

AI/ML engineer and data scientist with experience developing machine learning, NLP, RAG, and backend systems using Python, PyTorch, TensorFlow, Scikit-learn, FastAPI, and MongoDB. Worked across telecom analytics, healthcare NLP research, and end-to-end AI products involving model evaluation, retrieval, recommendation systems, and production deployment.

Experience spans model experimentation, evaluation, backend integration, and deployment of real-world AI applications — from 4G/5G anomaly detection and traffic forecasting at MasTec to hyperlocal community platforms, voice-memory apps, and medical chatbot research published at IEEE ACCAI 2024.

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Skills

Programming & Tools

JavaScript Python Git Postman Swift

AI & ML

TensorFlow NumPy Scikit-learn Keras Pandas PyTorch OpenCV Transformers Agentic Workflows & MCP RNN CNN RAG Pipeline FAISS LoRA LangChain Whisper

Cloud & DevOps

Google Cloud Firebase Functions Firebase Cloud Tasks MongoDB Atlas AWS Docker

Data & Backend

MongoDB SQL REST APIs FastAPI Caching Strategies Kafka Redis Node.js Express.js

Security & Infrastructure

Rate Limiting Input Sanitization Session & State Management

Platforms

Telegram Bot API Hugging Face Google Cloud API Firebase n8n Xcode

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Focus Areas

NLP & RAG Pipelines Retrieval & Recommendation Systems Telecom KPI Analytics Anomaly Detection & Forecasting Healthcare NLP Agentic Workflows & MCP ML Model Serving (FastAPI) Backend Integration & Deployment

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Experience

  • MasTec India LLP

    Data Scientist

    January 2023 – August 2024

    Built 4G/5G anomaly-detection pipelines by cleaning KPI data with Pandas, engineering statistical features, and training Scikit-learn models to identify abnormal cell-site behavior, while using Git for version control and collaborative development relevant to active sprints.

    Developed traffic/capacity forecasting models from utilization, throughput, and time-based features to predict congestion-prone sites and support proactive planning.

    Implemented RF analysis across RSRP, RSRQ, SINR, latency, handover success rate, and PRB utilization, producing site-level performance indicators for optimization teams.

    Automated feature-engineering and ETL pipelines from SQL/network logs using Python/NumPy, including normalization, encoding, rolling averages, trend features, and validation.

    Created Isolation Forest and clustering workflows for unsupervised anomaly detection and built FastAPI inference services exposing trained models through REST endpoints.

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Projects

Eventdude — The Event Handler

Winner

AI-powered event networking bot with multi-agent RAG matching, QR onboarding, and team formation. Miami Lamatic.ai Hackathon 2024.

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Publication

MEDOBOT · First Author · IEEE ACCAI 2024

Developed a medical chatbot for patient queries, medical question answering, appointment scheduling, and doctor recommendation. Fine-tuned and compared BERT and BioBERT using PyTorch and Hugging Face, with BioBERT outperforming BERT on the medical question-answering task.

Collaborated with doctors to collect, review, and validate medical question-answer data. Maintained separate training and benchmark datasets so evaluation examples were not exposed during model training. BioBERT achieved approximately 88% accuracy on the held-out evaluation dataset, with full system-level testing of response relevance and task completion.

View IEEE Publication

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Education

  • Florida Atlantic University

    Master of Science, Computer Science (Artificial Intelligence)

    Boca Raton, FL, USA · 3.8 CGPA · May 2026

  • Sathyabama Institute of Science and Technology

    Bachelors of Science, Electronics and Communication (Elective - Artificial Intelligence)

    Chennai, TN, India · 8.8 CGPA · May 2024

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Bookshelf

  • Deep Learning with Python by François Chollet
  • Make Your Own Neural Network by Tariq Rashid
  • Modern Robotics: Mechanics, Planning, and Control by Kevin M. Lynch and Frank C. Park

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Contact