About

Adhita Selvaraj is an experienced Infrastructure Engineer at Viaduct with a strong background in Containers, Cloud-orchestration, and Machine Learning. She is currently contributing to Kubeflow, the machine learning toolkit for Kubernetes, and is a main-contributor to dl-kops, a UI platform for getting started with machine learning on top of Kubernetes. With a focus on fair allocation of GPU resources, Adhita has also worked on a Kubernetes scheduler. Adhita has a passion for learning other tools, frameworks, and languages, and is proficient in Go, Python, and Swift. She has worked as a Software Engineer (Infra/ML) at Viaduct and as an ML Infrastructure Engineer at Cisco, where she was the Tech Lead for the Kubeflow onprem Working Group and the Cisco Kubeflow Starter Pack. Adhita also led joint efforts with AWS SageMaker team on Cisco-AWS Kubeflow Pipelines and designed a Kubeflow-based ML platform for private cloud servers. She has built and integrated tooling for creating, reviewing, deploying, and monitoring ML applications and created a CLI tool for scanning vulnerabilities as part of CI workflows in a Kubernetes cluster. Adhita has also prototyped and implemented the very first hybrid cloud Kubeflow pipelines (onprem → AWS SageMaker / GCP). Adhita holds a Master's Degree in Electrical Engineering from Stony Brook University and a Bachelor of Engineering in Electronics and Communication from Anna University. She is also fascinated by Python-based bots and text summarizers and has experience as an iOS Developer (Swift 3). Adhita's competencies include ML, infra, Kubernetes, Deep Learning, AWS, GCP, and Sagemaker. With 4.79 years of relevant experience, Adhita is a valuable asset to any team.