Roboflow
Dataset annotation and model training for object detection and classification
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I am an AI/ML and MLOps engineer with hands-on experience building scalable machine learning pipelines and ensuring data quality throughout the model lifecycle. My expertise includes data preprocessing, feature engineering, and handling data imbalance using techniques like SMOTE, all of which are crucial for preparing high-quality training data. I have developed end-to-end classification and regression systems, utilizing tools such as Scikit-Learn, Pandas, NumPy, and MLflow for experiment tracking and model versioning. My projects emphasize data reliability, automated testing (Pytest), and production monitoring (EvidentlyAI), ensuring that annotated data remains consistent and models are transparent with explainability tools like SHAP. I am passionate about automating workflows and maintaining rigorous standards for data integrity, making me well-suited for roles focused on data labeling and AI training data management.
Dataset annotation and model training for object detection and classification
Certificate, Artificial Intelligence and Machine Learning
Bachelor of Science, Mathematics
Insurance Sales man