Anirudh Ramanathan

As a senior software engineer at Rockset, I helped build core features and launch the cloud service in early 2019. 

• Led the product engineering team, building core features, APIs, authentication, resource management, multitenancy, role-based access control, billing and front-end systems.
• Launched several integrations with cloud data services to effectively load data and perform analytics using Rockset.
• Bootstrapped the customer success operation from the early days, channeling feedback from users into building new product features.
• Several talks and technical presentations to highly technical audiences.

As an early engineer on the Kubernetes and Google container engine team, I wore several hats - adding core functionality to Kubernetes , helping scale open source development, improving both internal and external processes, onboarding the SRE organization and eventually leading development on Big Data and Machine Learning applications in Kubernetes.

• Critical role in graduating StatefulSets to beta - Statefulsets are an important Kubernetes construct that allow running stateful applications on containers.
• Started and grew Spark on Kubernetes to a multi-organization effort and and eventually graduated into the Apache Spark project.
• Led the SIG Big Data community to contributors from several organizations, helping create an ecosystem of Spark, Airflow, Tensorflow, Jupyter and HDFS on Kubernetes.
• Scaled the Kubernetes project to contributions from a host of other organizations, rewrote Github automation, CLA infrastructure, etc.
• Invited speaker at several conferences & meetups.

Multiple Selections with Touchscreen Devices

• Carried out research on common UI interactions and their semantics with touch screen interfaces
• Developed an early prototype Android GUI library implementing the formalism, allowing a better and
  faster way to carry out multiple selections.
• Published work in NIK 2016.

• Implemented automation and tooling for NVIDIA's compute clusters used for hardware design and simulations.
• Improved core scheduling and resource allocation algorithms.
• Developed and maintained metrics and monitoring pipelines for clusters.
• Created tools to track resource planning, forecasting and utilization metrics and scaled it across all GPU and Mobile SoC projects.

GPA: 4.0 

Graduated with First Class Honors