Abhiraj Butala
Product Manager at Meta
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolAbhiraj Butala is a Principal Product Manager and former engineering lead with 12+ years building AI/ML-driven marketplaces and scalable platforms from early product-market fit to enterprise growth. He has led high-impact initiatives across recommendation systems, trust & safety, monetization, and location/data intelligence at Yelp and Walmart, and now drives organic business recommendations across Meta’s apps. Known for strong ownership and pragmatic execution, he has a track record of launching GenAI APIs and ML systems that meaningfully grew sales pipelines and protected users and advertisers from fraud and abuse. His engineering roots include leading pricing intelligence at Walmart and contributing DevOps improvements to the Alluxio open-source project, reflecting hands-on infrastructure and automation expertise. Based in the Bay Area, he combines product strategy, cross-functional stakeholder leadership, and technical depth to turn complex AI research into revenue-driving, production-ready products.
12 years of coding experience
12 years of employment as a software developer
BE Computer Engineering, BE Computer Engineering at Pune Institute of Computer TechnologyMS Computer Science, MS Computer Science at Stony Brook University
English, Hindi, Marathi
Stackoverflow
11reputation
49kreached
1answer
0questions
Github Skills (13)
sh10
bash10
script10
shell10
alluxio10
deployment-automation10
scripting10
vagrant9
orchestration8
orchestrate8
hadoop8
python6
data-analysis5
Programming languages (3)
Github contributions (5)
Alluxio/alluxio
Dec 2014 - Apr 2015
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
DevOps Engineer
DevOps EngineerContributions:19 commits, 7 PRs, 6 comments in 4 months
Contributions summary:Abhiraj's commits primarily focused on updating and modifying shell scripts related to the deployment and management of the Alluxio system. They replaced instances of "slave" with "worker" across various scripts, demonstrating an understanding of the system's architecture and deployment procedures. Additionally, the user adjusted configuration files, including those related to Hadoop and Vagrant, to ensure compatibility and proper setup for different deployment environments, showcasing a focus on infrastructure and automation.
data-analysisvirtual-distributed-filesystemanalyticsorchestrationdata-science
abhirajbutala/tachyon
Jan 2015 - Apr 2015
Contributions:54 pushes, 8 branches in 3 months
memorydistributed-storagereliablestoragedistributed
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