Nisarg Thakkar
Staff Software Engineer at LinkedIn
Pleasanton, California, United States
Summary
👤
Senior🎓
Top SchoolNisarg Thakkar is a Staff Software Engineer with 12 years of experience building scalable, resilient systems at LinkedIn, where he progressed from Software Engineer to Staff over four years. He combines strong backend expertise—Node.js, Java/Spring, Akka streams and high-throughput Kafka pipelines—with practical ML/CV experience from academic and defense projects, including contributions to the widely used OpenCV library fixing core image-processing and memory-management issues. A NYU MSCS graduate, Nisarg has led small teams to modernize legacy stacks and delivered production data streaming and archival solutions that run at tens of thousands of transactions per minute. Based in Pleasanton, CA, he enjoys tackling diverse, system-level problems end-to-end and is known for diving into obscure bugs and documentation gaps until they’re resolved.
12 years of coding experience
7 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and ScienceMaster of Science - MS Computer Science, Master of Science - MS Computer Science at New York UniversityHigh School Regular/General High School/Secondary Diploma Program, High School Regular/General High School/Secondary Diploma Program at Hiranandani Foundation School
English, Hindi, Marathi, Gujarati
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
computer-vision10
opencv10
c-language10
cprogramming-language10
image-processing10
documentation7
Programming languages (8)
Github contributions (5)
opencv/opencv
Jun 2014 - Apr 2015
Open Source Computer Vision Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 8 PRs, 14 comments in 10 months
Contributions summary:Nisarg primarily focused on bug fixes and code adjustments within the OpenCV library. They addressed issues related to dimension values, documentation errors, and incorrect step values for image processing, especially in multi-channel scenarios. The contributions modified core modules such as `core`, `imgproc`, and `videoio`, ensuring the library's functionality and documentation were improved. Several fixes involved the `release` function, which suggests contributions to memory management and object lifecycle within the library.
computer-visionc-plus-plusdeep-learningimage-processing
nisargthakkar/opencv
Jan 2015 - May 2016
Contributions:37 pushes, 17 branches in 1 year 4 months
image-processingpythoncomputer-visionvision
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