Tejas Patil
Software Engineer at The Apache Software Foundation
Menlo Park, California, United States
Summary
👤
Senior🎓
Top SchoolTejas Patil is a seasoned software engineer with 13 years of experience in large-scale distributed data processing and AI infrastructure, currently advancing GenAI platform work at Meta from Menlo Park. He co-founded and scaled Meta’s internal Spark team and has deep production expertise with Hive, Hadoop and Spark, contributing performance and reliability improvements upstream as an Apache Spark committer. His open-source contributions to high-profile projects like Apache Spark and Apache Nutch include optimizer and spill-reader performance tweaks, better error handling for external process integration, and crawler enhancements—work born from operating Spark at massive scale. At Meta he has led cross-team efforts to revamp model training stacks and now helps bridge Llama research into internal products, blending platform engineering with applied AI. Notably, his career pairs hands-on backend systems work with leadership in platform reliability, making him adept at turning research prototypes into reliable, scalable production services.
13 years of coding experience
13 years of employment as a software developer
BE IT, BE IT at Maharashtra Institute of TechnologyUniversity of California, Irvine
English, Hindi, Marathi
Stackoverflow
6,169reputation
887kreached
204answers
9questions
java
top-5%
algorithm
top-5%
hadoop
top-1%
Github Skills (27)
algorithm10
algorithms10
apache-spark10
web-crawler10
data-pipelines10
big-data10
hadoop10
data-structure10
java10
crawling10
scala10
javas10
performance-optimization10
data-structures10
data-pipeline10
Programming languages (3)
Github contributions (5)
apache/nutch
Jan 2013 - Feb 2014
Apache Nutch is an extensible and scalable web crawler
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 commits in 1 year
Contributions summary:Tejas contributed to the Apache Nutch web crawler project by implementing and modifying core functionalities. They added features to the fetcher component, specifically including crawl delay logging and integrating site-specific crawl delay configurations. Furthermore, the user modernized the project's architecture by delegating robots.txt parsing to the crawler-commons library and addressing deprecation warnings in the code base. They also fixed a bug involving duplicate temporary Hadoop files and updated the mime type detection.
scalableweb-crawlernutchosgiapache
apache/spark
Aug 2017 - Aug 2017
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 commit, 72 PRs, 619 comments in 1 day
Contributions summary:Tejas primarily contributed to the Apache Spark project's core functionalities, focusing on improving performance and resolving issues related to its processing capabilities. They worked on the `PipedRDD`, addressing exception handling and character encoding concerns for external process interactions. Their contributions also included optimizations such as speeding up shuffle service directory cleanup and introducing configurable buffer sizes for disk reads in the UnsafeSorterSpillReader. Furthermore, they made enhancements to the `ScriptTransformation` feature, ensuring better error reporting and improving the user experience.
analyticspythondata-processingsqlapache
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