• Worked as a part of an event processing infrastructure team powering Google Ads and Analytics.• Designed and implemented a generalized interface allowing users to easily write to various output sinks.

• Worked as a part of YouTube’s next-generation video processing infrastructure team.• Researched and prototyped a method to speed up initialization and save resources for batch (especially machine learning) tasks.• Would result in significant time and cost savings on most video processing across YouTube after deployment.

• Designed, wrote, and deployed a set of microservices (written in Java) on AWS.• Designed and developed an internal tool to predict the performance of job candidates using NLP and machine learning.• Improved the existing Secure@Source entity matching system by using machine learning instead of preset rules.

• Wrote Bash and R scripts to automatically process and analyze data from DNA sequencers.• Used Slurm to submit and manage jobs in the UC Riverside computing cluster.• Created a site using Django for users to submit samples.• Maintained and updated a PHP billing site.