Artificial Intelligence Engineer with experience in data analysis, model development, and MLOps. Skilled in Python, C++, TensorFlow, Keras, Scikit-learn, OpenCV, Power BI, Tableau, ML, and DL, with hands-on work on dashb…
Artificial Intelligence Engineer with experience in data analysis, model development, and MLOps. Skilled in Python, C++, TensorFlow, Keras, Scikit-learn, OpenCV, Power BI, Tableau, ML, and DL, with hands-on work on dashboards, model versioning, Kubeflow pipelines, MLflow, DVC, and Seldon Core.
Interpreted data and analyzed results utilizing statistical techniques to drive insights.
Spearheaded the implementation of advanced data analysis methodologies, resulting in a 40% reduction in data processing time and a 25% improvement in accuracy.
Constructed 10 reliable Power BI dashboards for managing and transforming data from various structured and unstructured sources, increasing data accessibility by 30%.
Executed model development in production, delivering 5 models with a 15% increase in accuracy compared to previous versions.
Performed model versioning and tracking using Git and model repositories, resulting in a 20% reduction in model deployment time.
Implemented an end-to-end MLOps pipeline, reducing deployment time by 40% and enhancing overall release efficiency by 30%.
Employed Data Versioning with DVC to manage and version datasets effectively, resulting in a 25% reduction in data management overhead.
Utilized MLflow to accurately track model versions, parameters, and performance metrics, achieving a 20% increase in model performance.
Designed end-to-end Kubeflow pipelines, automating the deployment process and reducing manual intervention by 50%.
Integrated Seldon Core into pipelines for deploying models as micro services with monitoring and scalability feature.
Achieved a 25% increase in model accuracy and enhanced precision by 15% for profile face detection in landmark models.
Trained pfld model on wlfw(98 annotated landmarks) and alfw(68 annotated landmarks) dataset to refine performance.
Increased model frame rate from 18fps to 60fps through rigorous refinement and optimization, resulting in superior outcomes for profile face landmarks.
Achieved a 70% increase in frame rate, enhancing real-time performance and enabling swift detection of facial landmarks.
Interpreting data, analyzing results using statistical techniques.
Developing and implementing data analyses, data collection
systems and other strategies that optimize statistical efficiency
and quality
model deployment in production.
Research and implement MLOps pipelines
Developing and managing data preprocessing pipelines.
Model versioning and tracking using Git and model repositories
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