Aindla Raju
AI/ML Engineer • Koratla, Telangana, India – 505326 • a**********@gmail.com • +91*******771 • drivetube.ai/•••••
Professional Summary
AI/ML Engineer with 0 years of experience applying machine learning, deep learning, and computer vision to build and deploy prototype models and web-based inference apps. Hands-on experience in Python, TensorFlow/Keras, Scikit-learn, Django, and end-to-end ML workflows including data preprocessing, model training, evaluation, and deployment.
Technical Skills
Programming Languages: Python,Java,C
Web Technologies: REST APIs
Frameworks and Libraries: TensorFlow,Keras,PyTorch,Scikit-learn,OpenCV,Pandas,NumPy,Matplotlib,Django,FastAPI
Databases: SQL,MySQL
Tools and Methodologies: Git,GitHub,Jupyter Notebook
Computer Vision and NLP: Convolutional Neural Networks,Data augmentation,NLP
ML Concepts and Methods: Ensemble methods,Hyperparameter tuning
Other AI Topics: Model evaluation,Regularization and dropout,LLM fine-tuning,Retrieval-Augmented Generation
Work Experience
Rinex
AI Intern
Jul 2025 – Aug 2025
AI intern at Rinex, a software company; supported machine learning workflows, model training, and prototype deployment for internal software projects.
Tech Stack: Python, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, OpenCV, Django, Git, Jupyter Notebook, Matplotlib
- Implemented end-to-end data preprocessing and feature engineering pipelines in Python using Pandas and NumPy to prepare tabular and image data for model training.
- Trained and validated supervised ML and deep learning models with Scikit-learn and TensorFlow/Keras; applied cross-validation and hyperparameter tuning to improve model generalization.
- Applied computer vision preprocessing with OpenCV and image augmentation to increase dataset diversity and improve classification robustness for image-based tasks.
- Built evaluation notebooks and automated metric reporting (accuracy, precision, recall, F1) using Matplotlib and Jupyter to support technical reviews and decision-making.
- Collaborated with engineers to integrate prototype models into web applications using Django and Git; assisted in creating REST endpoints for model inference.
- Documented experiments, maintained reproducible notebooks, and participated in code reviews and team syncs to align model improvements with project requirements.
Projects
Classification of Pests using Computer Vision (CNN Algorithm) | Jan 2025 – May 2025
Tools Used: Python, TensorFlow, Keras, Convolutional Neural Networks, Django, NumPy, Pandas, Matplotlib
- Designed and trained a CNN based on GoogLeNet (Inception) to classify agricultural pest types from images, achieving 93.78% accuracy on validation data.
- Implemented image preprocessing, augmentation, L2 regularization, and dropout to reduce overfitting and improve model reliability on small agricultural datasets.
- Deployed the trained model through a Django web app enabling farmers to upload images and receive immediate pest-type classification for actionable pesticide selection.
Ensemble Deep Learning Model for Vehicular Engine Health Prediction | Jun 2025 – Dec 2025
Tools Used: Python, TensorFlow, Keras, Scikit-learn, Random Forest, Pandas, NumPy, Django, MySQL
- Built ensemble models including Random Forest and soft-voting neural network ensembles to classify vehicular engine health from sensor signals (RPM, oil pressure, fuel pressure, coolant temperature).
- Evaluated model variants and found Random Forest achieved approximately 93% accuracy versus 63% for the ensemble neural network, guiding selection of the production model.
- Packaged the selected model and deployed it via a Django web interface allowing fleet operators to upload sensor data and receive real-time predictions with accuracy, precision, recall and F1 metrics.
Education
CMR Institute of Technology, Hyderabad
B.Tech. – Artificial Intelligence & Machine Learning • Hyderabad, India • 2022 – 2026
Certifications
Artificial Intelligence – Key Skills: Python, Machine Learning Concepts
Basics of Python
Explore Machine Learning using Python – Key Skills: Python, Machine Learning
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