• Developing tools to enable large scale ML on geospatial datasets with a focus on back-end services.

• Leading technical internationalization effort for a furniture recommendation strategy on Amazon.com. This includes expanding backend and frontend services to multiple regions, local dataset preparation, working with PMs in multiple regions for the localization of the UI

• Contributing to and designed components of a recommendation data pipeline built in AWS, deployed with CDK, utilizing Step Functions and implemented in Python

• Gaining valuable experience with Python, AWS, Typescript, Java, high TPS systems, data pipelines, designing and leading technical implementation of backend and frontend components

• Practicing DevOps on a DASH packaging web service written in Go, running in Kubernetes, deployed with helm, continuously delivered by Concourse, secured with Vault, and monitored by ELK, Prometheus and Jaeger.

• Collaborating with management and recruiting to interview candidates, plan engineering tasks, mentoring, and learning opportunities for the VIPER internship program.

• Working on live TV and video on demand packagers which collectively process hundreds of thousands of hours of video daily. Working with video standards like HLS, DASH, ISO-BMFF, MPEG-TS, h264, h256, and more.

• Contributing to, and helping manage various video and cloud related open source Go repositories.

Built, managed, and deployed a Selenium testing framework in Java for an ASP.NET web application. Reported, researched, and fixed bugs, gaining experience with C#, Javascript, NodeJS, WebSockets, Team Foundation Server, and other tools