Chinmay Kulkarni
Member Of Technical Staff at Microsoft AI
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolChinmay Kulkarni is a Member of Technical Staff at Microsoft AI with a decade of experience building web-scale ML and data infrastructure, currently focused on post-training, agents, and reinforcement learning orchestration. He specializes in training and serving large models at scale, distributed systems, and high-throughput data pipelines, having led LLM post-training infra at Inflection AI and model serving work at Microsoft. At Salesforce he engineered petabyte-scale observability pipelines and Trino ETL ingesting >3 GB/s, and his optimizations at People.ai drove a 4x throughput improvement for a core matching product. An active Apache contributor and Phoenix PMC member, he’s made meaningful backend and metadata-management fixes to widely used projects like Phoenix, HBase and Trino. Based in Sunnyvale, he pairs deep systems engineering with ML research roots from UIUC, and often bridges gaps between research prototypes and production-grade, cost-efficient platforms.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at COEP Technological UniversityMaster of Science (M.S.) with Thesis Computer Science, Master of Science (M.S.) with Thesis Computer Science at University of Illinois Urbana-Champaign
English, Hindi, Marathi
Github Skills (8)
javas10
hbase10
databases10
sql10
java10
database10
admin9
database-administration9
Programming languages (2)
Github contributions (5)
apache/phoenix
Nov 2017 - Dec 2020
Apache Phoenix
Role in this project:
Back-end Developer
Back-end DeveloperContributions:157 reviews, 186 commits, 94 PRs in 3 years 1 month
Contributions summary:Chinmay primarily focused on improving the Apache Phoenix database system by addressing specific issues and optimizing existing code. They removed redundant arguments in the `ConnectionQueryServicesImpl` class, improving code clarity. Furthermore, they worked on the schema management of Phoenix by preventing a mutex from being acquired in creating or dropping tables and views. They also contributed to the data integrity and synchronization of properties between the base table and index tables.
sqlapache-phoenixelixirapachebig-data
ChinmaySKulkarni/phoenix
Jun 2017 - Feb 2021
Mirror of Apache Phoenix
Contributions:483 pushes, 118 branches, 4 tags in 3 years 8 months
apache-phoenixelixirapachephoenixjava
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