Software Engineer2016 - PRESENTHFT firm
Technologies: Systems, Kernel Bypass, Architecture
- Led the entire team in the Singapore office.
- Took charge of connectivity with Asia markets, a major source of the company's revenue.
Software Engineer2016 - 2017Dgraph
Technologies: RocksDB, Raft Consensus Algorithm, gRPC, GoLand
- Decreased database data loading time by 60%. Previously, we were iterating over a hash map while trying to mutate it. As a result, we had to use lock-free hash maps, which are inherently slower than normal hash maps. I restructured the code such that there is no longer this contention. The code becomes simpler and faster as we can now use normal hash maps.
- Implemented many key features such as indexing, filtering, sorting, and pagination.
- Implemented new development practices that increased usability without compromising efficiency. With the addition of new features, it became clear that flatbuffers, which are immutable, are too painful to work with. I realized the team was not using and benchmarking protocol buffers correctly in the past, and did some analysis to show that protocol buffers, when used correctly, are no slower than flatbuffers. We switched and everyone was so glad that we don't have to deal with flatbuffers anymore.
- Piloted the Badger project, a Go LSM-tree key-value store. Implemented memtables, compaction, and the framework joining everything together. This project made it to the top ten list on HackerNews.
Senior Software Engineer2013 - 2016Google (Mountain View)
Technologies: Flume, MapReduce, Scikit-learn, C++, Machine Learning
- Worked on a team that used large scale machine learning to rank and price search ads, which is Google's main source of revenue. The goal was to increase satisfaction for advertisers and users by showing more relevant ads. Data-driven analysis and experiments were key to understanding the impact of our changes.
- Led a project to do offline feature computation with the help of query clustering. This led to an improvement in the AUC loss (a machine learning metric) by an impressive 26%, and an improvement in ads quality by 8% according to human raters.
- Rewrote the MapReduce pipeline for archiving advertisement landing page data. The new version achieved a greater than 10x speedup, and led to approximately $150 million increase in revenue per year.
- Reduced the amount of data being moved in our team's training pipeline, achieving a 2x speedup in the process.