• Orchestrated Docker and Kubernetes EKS Cluster development and maintenance to seamlessly support ML Model Pipelines for scalable production environments.

• Scaled cross-functional systems and feature stores during peak holiday seasons, handling traffic from over 150 million PS5 and PS4 consoles with zero on-call incidents, ensuring uninterrupted user experience.

• Enhanced security by implementing OAuth Integration and utilizing AWS Secrets Manager and IAM, ensuring secure access in a high-demand ML platform environment.

• Managed Kubeflow Pipelines for 5000+ concurrent Databricks - Apache Spark cluster deployments, enhancing model training, data processing capabilities, and ML infrastructure efficiency.

• Established CI/CD processes to enhance deployment efficiency and accelerate time-to-market for ML features using technologies like Bazel and Prow.

• Successfully delivered multiple features in a micro-service environment having worked on key aspects including API Design, Data Pipelines and support for 3rd Party features for SDWAN Orchestrator using Springbok Framework and REST APIs, along with modern services in Go Lang

• Delivered features and fixes for various cloud and on-prem services using Docker, Kubernetes and Jenkins for Build, Automation Testing and Deployment.

Working with Prof. Ron Artstein as the Course Producer for the Graduate Course CSCI 544 - Applied Natural Language Processing

• Built and integrated Test Automation suites for SDWAN Cloud Direct and integrated API endpoints for Network Discovery

• Contributed in the development of enterprise features for Azure cloud deployment on SDWAN Orchestrator and created REST API endpoints for customer access and subscription verification, hosted in separate Docker containers

• Implemented and documented steps for Behavior Driven Development and Testing for SDWAN Orchestrator using Behave in Python for security frameworks automation