---
title: "Dhruv Kabariya - Software Engineer 2 in Bengaluru | Tal"
description: "Meet Dhruv Kabariya, Software Development Engineer | Golang, Python, AWS, Kafka, Flutter | HLS Streaming, Microservices, AI, MCP, Agent based in Bengaluru. AI stack includes antigravity, claude code, and claude. Explore public work links including github."
image: "https://tal.club/meet/dhruv-kabariya/share-image"
---

# Dhruv Kabariya on Tal

## Headline

Software Development Engineer \| Golang, Python, AWS, Kafka, Flutter \| HLS Streaming, Microservices, AI, MCP, Agent

## About

I’m a Backend Software Engineer with 2\+ years of experience building and scaling low\-latency, high\-throughput backend systems using Golang, AWS, and distributed microservices\. I’ve worked on performance\-critical products where reliability and scale matter, including reducing API p95 latency from 7 seconds to 10 ms, re\-architecting video streaming pipelines to cut processing failures by 70%, and designing real\-time leaderboard and reward systems supporting 100K\+ concurrent users\. My experience spans Redis, Kafka, FFmpeg, CloudFront, IVS, PostgreSQL, and event\-driven architectures, with a strong focus on observability, cost optimization, and system resilience\. Previously, I built high\-frequency Golang microservices for real\-time location broadcasting, implemented Kafka\-based speech\-to\-text pipelines backed by custom ML models, and deployed computer\-vision services using FastAPI and PyTorch\. I’ve also delivered multiple Flutter applications used by 10K\+ daily users, giving me a strong product mindset and end\-to\-end ownership perspective\. I enjoy solving complex backend problems, optimizing systems at scale, and building clean, maintainable architectures, and I’m currently open to backend or platform engineering roles where I can work on challenging distributed systems and performance\-driven products

## Location

Bengaluru

## AI stack

antigravity

claude code

claude

cursor

langchain

claudecode

## Work experience

Software Engineer 2 at Loco, Mar 2025 \- Present · 1 y 6 mo, Bengaluru, Karnataka, India · Hybrid

Software Development Engineer \(Backend\) at Loco, Mar 2025 \- Jan 2026 · 11 mos, Bengaluru, Karnataka, India · Hybrid, • Feed API p95 latency from 7 sec to 10 ms by diagnosing Redis sorted\-set bottlenecks and optimizing it • Reduced log storage by 50% through log deduplication,index reduction, improved observability practices • Contributed to the monolith\-to\-microservices migration by developing the feeds Content Service • Re\-architected the HLS \- MP4 video pipeline, reducing processing failures by 70%, enforcing FFmpeg CPU limits, eliminating pod crashes, and avoiding a costly aws MediaConvert migration • Built a scalable Leaderboard service supporting 100K\+ concurrent users and 1K active leaderboards, handling scheduling, scoring aggregation, winner computation, rewards allocation, and sending notifications • Implemented a real\-time reward assignment system using an in\-house notification service, scaling to 50K\+ concurrent users and integrated with the platform’s reward engine\. • Secured CloudFront \+ IVS playback API, preventing misuse and saving $10K/day in IVS costs

Software Developer at 6th Labs, Apr 2023 \- Feb 2025 · 1 y 10 mo, India, Architected and deployed high\-performance microservices backend in Golang, handling 1000\+ concurrent user locations with gRPC streaming and Kalman filtering, achieving 99\.9% uptime Developed and published cross\-platform Flutter applications with background location tracking and gRPC integration, reducing battery consumption by 20% while maintaining seamless offline synchronization Implemented real\-time data processing pipeline using Kafka and Python consumers, integrating Wav2Vec speech\-to\-text models for audio stream processing at scale Led AWS infrastructure deployment with EC2, load balancing, and auto\-scaling groups, ensuring robust scalability and establishing comprehensive CI/CD pipelines that improved development efficiency by 30% Spearheaded development of AI\-powered traffic violation detection system using YOLO models, processing thousands of images daily with 95% accuracy and automated reporting Integrated ChromaDB for vector\-based search capabilities, enabling AI\-driven recommendation systems that increased product discovery rates by 35% Architected and deployed WhatsApp/Telegram sales bot integrating LLM models and RAG for intelligent product discovery, resulting in 40% increase in automated customer interactions Optimized database performance through advanced indexing and query optimization, reducing API response times by 40% while maintaining data integrity across services

Research Intern at Ahmedabad University, Nov 2020 \- Feb 2021 · 4 mos, Ahmedabad, Gujarat, India, During my tenure at Ahmedabad University, I undertook a research internship that honed my skills in data processing and computer vision\. My responsibilities included: Data Acquisition and Labeling: I developed web scraping tools to collect extensive datasets, which I meticulously labeled to ensure high\-quality inputs for model training\. Model Fine\-Tuning: Leveraging PyTorch, I fine\-tuned the YOLOv5 model for object detection tasks, adapting it to our specific dataset to enhance its performance\. Model Evaluation: I conducted comparative analyses of various text recognition models, assessing their accuracy and efficiency to identify the most suitable model for our applications\. Object Classification: I implemented and evaluated different object classification algorithms to improve the system's ability to accurately categorize detected objects\. This experience provided me with a solid foundation in computer vision techniques and practical expertise in utilizing PyTorch for model development and evaluation\.

## Education

Bachelor of Engineering \- BE, Computer Science, Ahmedabad University

## Public links

- github: https://github\.com/dhruv\-kabariya

[View the original profile](https://tal.club/meet/dhruv-kabariya)

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