R&D engineer
Its mentoring and contious project
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Machine Learning Engineer with hands-on experience in preparing and optimizing training data for computer vision, NLP, and RAG systems. Worked on medical image classification (Parkinson’s detection), EEG-based Alzheimer’s prediction, and custom dog-disease dataset creation—handling data cleaning, label structuring, class imbalance, augmentation, and CNN-ready preprocessing. Built RAG pipelines by cleaning and chunking domain documents, generating embeddings, and aligning content for vector databases to improve retrieval relevance. Experienced in end-to-end ML workflows including data collection, annotation design, model training, evaluation, and API-based deployment. Technologies: Python, TensorFlow/Keras, Scikit-learn, CNNs, NLP preprocessing, Embeddings, Vector Databases, RAG pipelines, Django/FastAPI (model serving), SQL/MySQL, data augmentation, feature engineering.
Its mentoring and contious project
it was to annaotate for yolo v8 model
Diploma in Electrical and Electronics Engineering, Electrical and Electronics Engineering
Bachelor of Technology, Electrical and Electronics Engineering
Machine Learning Engineer
AI Intern