
Arpit Agarwal developed two core platform features for the Meesho/BharatMLStack repository, focusing on real-time data processing and performance measurement. He implemented an online feature store Kafka consumer using Go and Docker, setting up logging, metrics, and a Kafka listener to process normalized entities efficiently. To streamline engineering workflows, he also created a Bash-based benchmark automation script that runs Go benchmarks with versioned outputs and optional profiling, supporting both targeted and full-suite execution. Arpit’s work demonstrated depth in distributed systems, microservices, and profiling, delivering foundational capabilities that enhance both product reliability and engineering efficiency within a one-month period.

May 2025 (Meesho/BharatMLStack) focused on delivering two key platform capabilities to enable reliable real-time feature processing and standardized performance measurement, driving both product value and engineering efficiency.
May 2025 (Meesho/BharatMLStack) focused on delivering two key platform capabilities to enable reliable real-time feature processing and standardized performance measurement, driving both product value and engineering efficiency.
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