Sachchit Kunichetty is a performance engineer based in Chicago with five years of hands-on experience optimizing software and data pipelines for low-latency, high-throughput environments. Currently at IMC Trading, he brings a pragmatic mix of systems performance tuning and data engineering honed through internships at Wolverine and Mage and teaching roles at the University of Michigan. His open-source contributions to the popular Mage-AI project improved data cleaning, type handling, imputation, and collinearity removal—practical work that boosts pipeline reliability and model readiness. Comfortable bridging research-minded microstructure interests and production constraints, he combines academic rigor with a track record of shipping bug fixes and performance improvements under real trading and data workloads.
5 years of coding experience
Bachelor of Science in Engineering, Bachelor of Science in Engineering at University of Michigan College of Engineering
đź§™ Build, run, and manage data pipelines for integrating and transforming data.
Role in this project:
Data Engineer
Contributions:165 reviews, 105 commits, 166 PRs in 2 months
Contributions summary:Sachchit primarily contributed to the development and improvement of data cleaning and transformation functionalities within the Mage AI platform. They focused on implementing and refining cleaning rules, particularly for handling column names and data type conversions. The user also introduced new imputation strategies and contributed significantly to the quality and performance of the data cleaning pipeline, including bug fixes. Furthermore, the user added a rule for removing collinear columns to increase data quality.
Contributions:38 PRs, 41 pushes, 15 branches in 1 year 10 months
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Sachchit Kunichetty - Performance Engineer at IMC Trading