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Ranjith Kumar Reddy Kotireddy

Machine Learning Engineer • India • k***************@gmail.com • +91*******936 • drivetube.ai/•••••

Professional Summary

Machine Learning Engineer with 0 years of experience building ML, NLP, and model-deployment solutions using Python, TensorFlow, PyTorch, and Azure. Experienced in end-to-end model development including data preprocessing, feature engineering, model training, REST API deployment, and interactive visualizations. Seeking an entry-level ML role to contribute applied ML solutions and scalable model delivery.

Technical Skills

Programming Languages: Python,C++
Frameworks and Libraries: TensorFlow,Keras,PyTorch,Scikit-learn,XGBoost,Flask,FastAPI,OpenCV,NumPy,Pandas,Matplotlib,Seaborn
Databases: SQL
Cloud and DevOps: Microsoft Azure,Model Deployment,REST API Development,Model Serving
Data and Analytics: Data Preprocessing,Feature Engineering,Supervised Learning,Deep Learning,Computer Vision,Natural Language Processing,Model Evaluation,Plotly,Power BI,Data Visualization
Tools and Methodologies: Jupyter Notebook,VS Code,Eclipse,Git,GitHub
Core Concepts: Statistical Analysis,Cross-Validation,Hyperparameter Tuning,SDLC

Work Experience

Freelancer
Remote / India
Machine Learning Engineer
Mar 2025 – Present
Independent ML consultant delivering NLP and ML model development, deployment, and analytics solutions for small clients and prototypes.
Tech Stack: Python, TensorFlow, PyTorch, Scikit-learn, Flask, FastAPI, Power BI, NumPy, Pandas, Plotly, Git, Jupyter Notebook
  • Designed and implemented NLP solutions including chatbots, sentiment analysis, and text classification using Python, Scikit-learn, TensorFlow and PyTorch; built preprocessing pipelines for tokenization and embeddings.
  • Packaged trained models as REST APIs using Flask and FastAPI to enable programmatic access and automation of inference workflows.
  • Constructed end-to-end model training workflows with cross-validation and hyperparameter tuning to improve model generalization and stability.
  • Integrated model outputs into interactive visualizations and dashboards using Plotly and Power BI for stakeholder review and insights.
  • Optimized preprocessing and inference code to streamline prototype deployments and reduce manual intervention during scoring.
  • Maintained reproducible work via Jupyter notebooks, Git version control, and README documentation for client handoffs.
Coincent
Bengaluru, India
Machine Learing Intern
Sep 2024 – Feb 2025
Worked on machine learning algorithms for autonomous driving / self-driving vehicle research and prototyping.
Tech Stack: TensorFlow, PyTorch, Keras, Python, NumPy, Pandas, Jupyter Notebook, Git
  • Developed perception algorithms for autonomous driving prototypes using TensorFlow and PyTorch, focusing on image-based object detection and classification tasks.
  • Improved model accuracy by 12% through targeted data augmentation, feature engineering, and hyperparameter tuning on training sets.
  • Optimized ML training and preprocessing pipelines, reducing end-to-end processing time by 30% via vectorized operations and optimized batching.
  • Built and evaluated custom CNN and transfer-learning models for camera-based inputs using TensorFlow and Keras to enhance detection robustness.
  • Implemented reproducible experiment workflows and evaluation scripts using Jupyter notebooks and Git to standardize model comparisons.
  • Documented model performance and produced visualizations to communicate results and recommended next steps for model integration.

Projects

Credit Card Fraud Detection | Jan 2025 – Jan 2025
Tools Used: Python, Scikit-learn, XGBoost, Flask, Power BI, Pandas, NumPy
  • Developed a fraud detection pipeline using feature engineering and XGBoost, achieving 92% accuracy on test data.
  • Deployed the trained model as a REST API with Flask to enable real-time scoring and batch processing.
  • Created Power BI dashboards to visualize anomalies, transaction patterns, and customer segments for business stakeholders.
Traffic Sign Classification | Jul 2024 – Jul 2024
Tools Used: OpenCV, Scikit-learn, Python, NumPy, Pandas
  • Built an image classification system for traffic signs using OpenCV for preprocessing and Scikit-learn for modeling.
  • Applied image processing techniques and feature extraction to improve signal-to-noise ratio and classifier performance.
  • Evaluated multiple models and preprocessing pipelines to select the best performing approach for deployment.
Event Planning Management Website (AI-based Voice Assistant) | Jun 2024 – Jun 2024
Tools Used: Python, Speech Recognition Libraries, NLP, Flask
  • Developed an AI voice assistant capable of parsing and executing user voice commands for event planning tasks.
  • Implemented NLP pipelines to interpret intents and map voice inputs to application functions.
  • Structured modular, object-oriented code to enable extension of new voice commands and actions.

Education

Amity University Madhya Pradesh, Gwalior
Bachelor of Technology in Computer Science Engineering (AI & ML) • Gwalior, India • July 2020 – July 2024
Sri Chaitanya Junior College, Tirupati
Intermediate (PCM) • Tirupati, India • May 2018 – April 2020

Certifications

Power BI Data Analyst — Microsoft • Mar 2025
Azure Fundamentals — Microsoft • Feb 2024

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