Software Engineer & Technical Leader with a focus on distributed systems and machine learning. I am passionate about start-ups and entrepreneurship. Currently, I work on the future of databases at Rockset and serve as an advisor to Doc.ai.
I made key contributions to Kubernetes Core Controllers (StatefulSet, ReplicaSet, Deployment, DaemonSet), Big Data and Machine Learning on containers. I started and led the community to create the Kubernetes Scheduler project in Apache Spark, was a founding engineer on the Kubeflow Project, and provided architectural leadership to containerize Big Data workloads like Apache Airflow, HDFS and Jupyter.
I’m a committer on Apache Spark with a focus on enhancements to the core scheduling primitives and the kubernetes cluster manager within Spark.
For two years till June 2018, I worked at Google on Google Kubernetes Engine (GKE). As an early member of the GKE team, I wore several hats, handling roles from product management to release engineering to being point-of-contact for external customers as the team grew. I also spent a couple of years prior to that working on infrastructure at Nvidia.
I have a Master’s degree in Computer Science from Texas A&M University and a Bachelor’s Degree from the Indian Institute of Technology (BHU).
Check out my full CV.