• Senior AI/ML Engineer and Data Scientist with 12+ years of experience designing, developing, deploying, and operating enterprise-scale Artificial Intelligence, Machine Learning, Generative AI, Computer Vision, and cloud-native data platforms across healthcare, financial services, telecom, and enterprise environments. • Extensive hands-on experience with Azure Databricks, Apache Spark, PySpark, Delta Lake, Azure Data Factory, Azure Machine Learning, Azure Synapse Analytics, Azure Functions, Azure Blob Storage, and Azure cloud services for scalable AI/ML and data engineering workloads. • Strong expertise building end-to-end AI/ML solutions on Azure Databricks, including large-scale data processing, feature engineering, model training, experimentation, inference pipelines, model validation, and production deployment. • Advanced Python development experience using PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, Transformers, FastAPI, Flask, and related AI/ML frameworks. • Hands-on knowledge of Computer Vision / Vision AI techniques including CNNs, transfer learning, OCR, object detection, YOLO, Faster R-CNN, image segmentation, U-Net, Mask R-CNN, ResNet, VGG, MobileNet, and image preprocessing. • Strong understanding of deep-learning architectures, including Artificial Neural Networks, CNNs, Autoencoders, Transformers, Attention Mechanisms, LSTMs, and transfer-learning models, with hands-on PyTorch and TensorFlow experience. • Designed and deployed production-grade Machine Learning and Deep Learning systems supporting real-time inference, predictive analytics, recommendation engines, classification, anomaly detection, forecasting, healthcare risk prediction, and intelligent automation. • Experienced in building scalable ML pipelines using Azure Databricks, MLflow, Apache Airflow, Azure Machine Learning, Spark, Delta Lake, Docker, Kubernetes, and CI/CD.…• Senior AI/ML Engineer and Data Scientist with 12+ years of experience designing, developing, deploying, and operating enterprise-scale Artificial Intelligence, Machine Learning, Generative AI, Computer Vision, and cloud-native data platforms across healthcare, financial services, telecom, and enterprise environments. • Extensive hands-on experience with Azure Databricks, Apache Spark, PySpark, Delta Lake, Azure Data Factory, Azure Machine Learning, Azure Synapse Analytics, Azure Functions, Azure Blob Storage, and Azure cloud services for scalable AI/ML and data engineering workloads. • Strong expertise building end-to-end AI/ML solutions on Azure Databricks, including large-scale data processing, feature engineering, model training, experimentation, inference pipelines, model validation, and production deployment. • Advanced Python development experience using PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, Transformers, FastAPI, Flask, and related AI/ML frameworks. • Hands-on knowledge of Computer Vision / Vision AI techniques including CNNs, transfer learning, OCR, object detection, YOLO, Faster R-CNN, image segmentation, U-Net, Mask R-CNN, ResNet, VGG, MobileNet, and image preprocessing. • Strong understanding of deep-learning architectures, including Artificial Neural Networks, CNNs, Autoencoders, Transformers, Attention Mechanisms, LSTMs, and transfer-learning models, with hands-on PyTorch and TensorFlow experience. • Designed and deployed production-grade Machine Learning and Deep Learning systems supporting real-time inference, predictive analytics, recommendation engines, classification, anomaly detection, forecasting, healthcare risk prediction, and intelligent automation. • Experienced in building scalable ML pipelines using Azure Databricks, MLflow, Apache Airflow, Azure Machine Learning, Spark, Delta Lake, Docker, Kubernetes, and CI/CD.WWWW…