Ankur Agrawal
Staff Software Engineer, ML Infra at LinkedIn
California, United States
Summary
🤩
Rockstar🎓
Top SchoolAnkur Agrawal is a Staff Software Engineer based in California with 10 years of experience building large-scale distributed systems, storage, and machine learning infrastructure at LinkedIn. He leads efforts to architect next-generation ML infra, having previously driven blobstore and datalake platforms and contributed backend improvements to the well-known linkedin/ambry distributed object store. His background spans low-level systems work—file systems, OS, security—and high-scale data platform design, giving him a rare combination of systems depth and distributed-data pragmatism. Ankur’s career includes cloud compute and security development at Oracle and performance-focused storage engineering at Intel and Axcient, reflecting a consistent focus on reliability and scalability. He pairs hands-on implementation skills with technical leadership, and holds advanced training in AI from Stanford and an MS in Computer Science from Stony Brook.
10 years of coding experience
14 years of employment as a software developer
Master of Science Computer Science, Master of Science Computer Science at Stony Brook UniversityGraduate Certificate in Artificial Intelligence, Graduate Certificate in Artificial Intelligence at Stanford University
Github Skills (12)
javas10
api-rest10
rest-api10
backend10
api-design10
restful-api10
java10
cloud-storage10
jtest10
testing10
microsoft-azure9
azure9
Programming languages (4)
Github contributions (5)
linkedin/ambry
Jun 2019 - Sep 2022
Distributed object store
Role in this project:
Back-end Developer
Back-end DeveloperContributions:707 reviews, 140 commits, 362 PRs in 3 years 3 months
Contributions summary:Ankur primarily focused on enhancing the functionality and performance of the backend system. Their contributions centered around implementing features to support a new blob size header in the API, and included corresponding changes in frontend tests. Additionally, the user improved the performance of PUT requests by implementing random partition selection. They also added core get functionalities for the Azure VCR and were responsible for creating the main class and other relevant configurations.
osgidistributed-systemsobject-storedistributed-object-storejava
ankagrawal/ambry
Jun 2019 - Nov 2024
Distributed object store
Contributions:1 PR, 1193 pushes, 244 branches in 5 years 6 months
distributed-systemsobject-storedistributed-object-storedistributed
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