Built improved location filtering for talent discovery search using elasticsearch, GraphQL, and React.

Developed healthy habits, community service, and tech projects to enrich the foundational infrastructure of my personal life and community.

Machine Learning Platform: A system for ML product developers to write code, fetch signals, specify model configs, and run experiments and production inference (~500 machine scale). Highlights: * Principally responsible for designing and building out the real time ML inference platform. Worked closely with product and ML engineers to enable ranking and recommendation use cases.* Helped develop the signal aggregation system used to compute ML feature vectors using HBase, Kafka and Spark. Designed and built the signal fetcher for inference, and drove the next generation generic signal aggregator.* Led a 3-person team to define perf and reliability targets for release. Then productionized, optimized, and scaled several new & legacy prod systems to 20x their load ahead of a major product launch (~500 machine scale).

Coredata: A storage system consisting of ~5000 machines holding trillions of objects, petabytes of data, and handling 10M QPS at (~ms) latency. Consists of Edgestore (in-house NoSQL store), sharded MySQL databases, and caching. Highlights:* Responsible for executing a reliability overhaul of database caching and parts of Edgestore caching. Developed memcache ops tooling, telemetry, consistency verification, and database dual caching to fix a major source of site outages while growing to 5M QPS and enabling a 99.999% Edgestore uptime SLO.* Built much of the monitoring, deployment, integration testing, multi-tenancy tooling, and much Edgestore functionality that enabled a rich feature set and scale 10x to ~5000 machines.Multihoming: Rearchitecting databases and services to serve and failover traffic across regions.* Principally responsible for designing & building a traffic routing layer, cross-team data locality analysis, and driving the read-only Edgestore failover project during its later stages (~1000s machine scale).* Helped bootstrap the East Coast and EU presence, optimized perf, and built much of the test infrastructure.

Built a feature of secondary indexing in DynamoDB, a fast and scalable NoSQL database service.

Developed back-end web services.

Built new test framework features for Google App Engine.

Built scalable data back-end features using AWS, Cassandra, and Hadoop.

Helped develop website features and browser plug-ins.

Patiently helped peers in their university physics courses as a paid physics tutor.