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U.Chennaiah

Machine Learning Engineer • Neelahalli, Jogulamba, Gadwal, Telangana 509125, India • u**********@gmail.com • 773****310 • linkedin.com/••••• • github.com/•••••

Career Objective

Machine Learning Engineer (fresher) with hands-on experience building and deploying end-to-end ML pipelines, production REST APIs, and RAG-based LLM applications. Practical experience with Python, Scikit-learn, XGBoost, LangGraph, ChromaDB, FastAPI, Docker, and MLflow; delivered IoT-integrated AI solutions and tracked reproducible experiments. SAP Certified Data Analyst with SQL and data-visualisation skills, seeking an ML Engineer role to apply production-grade modelling, MLOps practices, and API deployment to solve business problems at scale.

Education

Lovely Professional University
Bachelor of Technology in Computer Science and Engineering • Phagwara, Punjab • 2022 – 2026
Prathibha Junior College
12th with Science • Mahabubnagar, Telangana • 2020 – 2022
Montessori Traditions High School
10th with Science • Gadwal, Telangana • 2019 – 2020

Technical Skills

Programming Languages: Python,Java
Web Technologies: REST API
Frameworks and Libraries: Scikit-learn,FastAPI,Flask,Pandas,NumPy,Matplotlib,Seaborn
Databases: SQL,MySQL,MongoDB
Cloud and DevOps: Docker,Docker Compose,CI,CD fundamentals
Data and Analytics: XGBoost,Random Forest,KNN,Naive Bayes,Linear Regression,Tableau,Excel
Tools and Methodologies: Git,GitHub
Skills: LLMs,Retrieval-Augmented Generation,LangGraph,Vector databases,ChromaDB
MLOps & Model Management: MLflow,Experiment tracking,Model versioning
Embedded Systems & IoT: Arduino,Raspberry Pi,Sensor data integration,OpenWeatherMap API
NLP & Speech: Semantic search,Speech-to-text integration
Other: Cloud computing,Model evaluation & cross-validation,Data preprocessing & feature engineering

Projects

Smart Irrigation System Using AI and IoT | Feb 2026 – Apr 2026
Tools Used: Python, Scikit-learn, Naive Bayes, MLflow, FastAPI, Docker, Arduino, Raspberry Pi, OpenWeatherMap API, Pandas, NumPy, Matplotlib
  • Trained a Naive Bayes classifier using real-time soil moisture, temperature, and weather sensor data streamed from Arduino and Raspberry Pi; achieved an F1-score of 0.91 using 5-fold cross-validation.
  • Engineered multi-sensor fusion features and tuned classification thresholds to handle imbalanced pump on/off triggers, improving decision reliability across wheat and maize plots.
  • Validated system in a 30-day controlled field test and reduced irrigation water consumption by 43% compared to baseline through model-driven pump scheduling.
  • Packaged the trained model as a low-latency REST endpoint with FastAPI and containerised the service using Docker; average inference latency reduced to under 200ms.
  • Implemented experiment tracking and model versioning with MLflow for full reproducibility across 12 training runs, logging hyperparameters, metrics, and artifacts.
MediAssist — AI-Powered Medical Chatbot | Jan 2025 – Apr 2025
Tools Used: Python, FastAPI, Flask, LangGraph, ChromaDB, RAG, LLMs, MLflow, Docker, Docker Compose, Speech-to-text
  • Built a Retrieval-Augmented Generation (RAG) medical Q&A system using ChromaDB for semantic retrieval over curated medical knowledge, achieving 87% response relevance on a 500-query held-out test set.
  • Designed a multi-agent reasoning pipeline with LangGraph that reduced low-confidence hallucinations by 35% versus a baseline single-agent LLM, validated through manual review of 200 edge-case queries.
  • Containerised the FastAPI/Flask backend and ChromaDB with Docker Compose to deploy a reproducible REST API serving concurrent users with average response time under 1.8s.
  • Implemented confidence-based fallback routing that chains VectorDB, Wikipedia, and live web search for uncertain queries, improving answer accuracy on ambiguous inputs.
  • Extended the assistant to support 3 languages and integrated a speech-to-text module to enable voice input, increasing simulated multilingual reach by 60% in tests.

Certifications

SAP Certified — Data Analyst, SAP Analytics Cloud (SAP SAC) — SAP • Mar 2026
Machine Learning with Python — Cognitive Classes • Apr 2025
Cloud Computing Certification — NPTEL • Mar 2024

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