- Developed and automated an end-to-end MLOps pipeline on Google Cloud Vertex AI, utilizing Docker and Kubeflow Pipelines for efficient model training, deployment, and monitoring of Text-to-Speech models.- Optimized GPU resources for PyTorch-based model training, enhancing workflow efficiency and deploying high-performance AI solutions at scale on cloud endpoints.- Implemented CI/CD pipelines with tools like Google Cloud Build and DVC, ensuring robust version control, continuous… Show more - Developed and automated an end-to-end MLOps pipeline on Google Cloud Vertex AI, utilizing Docker and Kubeflow Pipelines for efficient model training, deployment, and monitoring of Text-to-Speech models.- Optimized GPU resources for PyTorch-based model training, enhancing workflow efficiency and deploying high-performance AI solutions at scale on cloud endpoints.- Implemented CI/CD pipelines with tools like Google Cloud Build and DVC, ensuring robust version control, continuous integration, and streamlined deployment for seamless machine learning operations.- Collaborated cross-functionally to integrate AI models with production systems, focusing on best practices in data handling, model serving, and scalability across cloud-based environments. Show less

- Delivering expertise in data mining techniques, including clustering, classification, and predictive modeling.- Leading hands-on lab sessions with industry-standard tools (Python, R, SQL) to bridge theory and real-world applications.- Mentoring students for professional readiness by fostering critical thinking and technical skills.- Supporting technological proficiency by empowering students to use key data science tools and software platforms.

- Developed scalable ML pipelines using Google Cloud Dataflow and Vertex AI, automating model retraining and deployment workflows to accelerate delivery of predictive insights.- Created a predictive maintenance solution leveraging Google Cloud IoT Core and BigQuery ML, reducing unexpected downtime by forecasting equipment failures in real-time.- Built LLM pipelines for text extraction in medical reports, automating data processing and reducing manual handling time by 70%.- Optimized… Show more - Developed scalable ML pipelines using Google Cloud Dataflow and Vertex AI, automating model retraining and deployment workflows to accelerate delivery of predictive insights.- Created a predictive maintenance solution leveraging Google Cloud IoT Core and BigQuery ML, reducing unexpected downtime by forecasting equipment failures in real-time.- Built LLM pipelines for text extraction in medical reports, automating data processing and reducing manual handling time by 70%.- Optimized model training on GKE with GPU acceleration and Autoscaling, achieving a 40% reduction in cloud costs while enhancing performance.- Implemented customer sentiment analysis using Google Cloud’s Natural Language API and BigQuery, providing insights to improve product strategies and customer satisfaction. Show less

- Designed and deployed a cloud-native document processing solution on Google Kubernetes Engine, enhancing scalability and document management efficiency for healthcare and legal sectors.- Architected microservices infrastructure using Helm charts on GKE, enabling seamless multi-cloud deployments and improved product scalability.- Streamlined CI/CD workflows using GitOps practices with Cloud Build and ArgoCD, reducing deployment times and ensuring consistent software releases.-… Show more - Designed and deployed a cloud-native document processing solution on Google Kubernetes Engine, enhancing scalability and document management efficiency for healthcare and legal sectors.- Architected microservices infrastructure using Helm charts on GKE, enabling seamless multi-cloud deployments and improved product scalability.- Streamlined CI/CD workflows using GitOps practices with Cloud Build and ArgoCD, reducing deployment times and ensuring consistent software releases.- Established centralized monitoring and logging using Google Cloud Operations Suite, enabling proactive monitoring and improving system reliability.- Automated testing workflows with PyTest and Cloud Build, decreasing manual testing efforts by 60% and ensuring robust software quality. Show less

- Developed an event-driven integration pipeline with Google Cloud Functions and Eventarc, optimizing data synchronization across platforms and reducing latency.- Implemented a workflow orchestration system using Cloud Composer, automating complex data processing tasks and minimizing operational errors.- Built a Slack bot integrated with Google Cloud Functions and Dialogflow, automating task notifications and improving team productivity by 50%.- Designed a data transfer monitoring… Show more - Developed an event-driven integration pipeline with Google Cloud Functions and Eventarc, optimizing data synchronization across platforms and reducing latency.- Implemented a workflow orchestration system using Cloud Composer, automating complex data processing tasks and minimizing operational errors.- Built a Slack bot integrated with Google Cloud Functions and Dialogflow, automating task notifications and improving team productivity by 50%.- Designed a data transfer monitoring system with BigQuery and Cloud Monitoring, ensuring data integrity and transparency across systems.- Enhanced the efficiency of event-driven architectures by implementing a configuration-driven framework with Eventarc, reducing unnecessary event triggers by 1000+ daily. Show less