Yashashwini Dixit

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Building scalable systems & AI-powered solutions
Passionate about clean architecture, performance optimization, and creating impactful technology.

About Me

Software Engineer with 2+ years of hands-on experience building scalable web and mobile applications across healthtech, AI, and platform development domains. Skilled in full-stack development with expertise in .NET, React, Python, and cloud technologies.

Currently contributing to enterprise-scale projects at Providence India, including an AI-powered network management system handling 40K+ devices and a real-time analytics platform aggregating data from 3000+ teams. Strong focus on clean architecture, performance optimization, and solving complex technical challenges.

Technical Arsenal

C++

Java

Python

JavaScript

.NET

React

React Native

Ruby on Rails

NoSQL/SQL

DevOps

Linux

Azure Cloud

System Design

AI/ML Integration

DSA
350+ LeetCode, Striver A2Z

🚀 Currently Exploring

Deep diving into Generative AI and LLMs to become an AI Generalist. Exploring LangChain, prompt engineering, RAG systems, and building intelligent applications that leverage the power of modern AI.

Career Journey

Providence India

Software Engineer 2

April 2025 - Present

  • Currently working on AI-powered network management system managing 40K+ network devices with LLM-based AI agent for natural language queries, featuring interactive diagrams, graph views, and IP lookup for 1.1M+ devices - reducing manual operations by 60%
  • Core contributor to company-wide analytics platform consolidating real-time engineering metrics across 3000+ teams, enabling data-driven strategic decisions for leadership

Providence India

Software Engineer

July 2023 - March 2025

  • Engineered .NET APIs powering platform for 120K+ users, facilitating supporter-peer matching (75+ supporters per request currently), request workflows, email notifications, and admin dashboards
  • Ensured HIPAA compliance via secure Azure triggers and optimized PDF export APIs with rate limiting and payload compression (73% reduction)
  • Enabled Okta OAuth SSO across 5+ sign-in options and built Ruby on Rails APIs for user provisioning
  • Mentored junior engineers on .NET design patterns and SOLID principles
  • Engineered dual-layer encryption (symmetric + asymmetric) for secure authentication flows

Providence India

Software Engineer Intern

January 2023 - June 2023

  • Implemented backend .NET APIs for patient-caregiver POC app using Azure AI services and CosmosDB, achieving <200ms response times for location-based provider recommendations
  • Contributed to React Native Web frontend for cross-platform mobile experience

FarmwiseAI

Full Stack Developer Intern

October 2022 - December 2022

Created React Native Android app deployed by Tamil Nadu Government with live video streaming and GPS tracking for agricultural assessments, improving field data reporting speed by 70%.

Samsung R&D Institute India

Research & Development Intern

November 2021 - October 2022

  • Implemented multilingual Q&A chatbot in Rasa with custom NLU and ASR using SpaCy, FastText, and Jarvis
  • Developed natural language model for English-Marathi conversation, increasing response accuracy for Marathi queries by 25% on 10K+ annotated conversations

Providence India

Software Engineer Intern

May 2022 - July 2022

Explored Microfrontend architecture using Single-SPA to develop modular, independently deployable UI components, enabling seamless collaboration across teams.

Valuefy Solutions

Software Developer

January 2022 - July 2022

Revamped the React Native wealth management app by redesigning core UI flows, implementing responsive dashboards, and integrating real-time financial data APIs. Enhanced user experience, security, and performance for cross-platform deployment.

Education

Bachelor of Technology in Computer Science and Engineering

Vellore Institute of Technology, Chennai

2019 – 2023  |  CGPA: 8.86

Personal Projects

E-Classroom (EDEZE)

Developed a classroom application featuring web-proctored exams, assignment submission, performance analysis, and feedback functionalities.
GitHub Link

HTML CSS JavaScript Django

Automatic Attendance System

Built a facial recognition-based attendance system using OpenCV, Tkinter, PIL, and Pandas, automating student attendance with manual entry and export features.
GitHub Link

OpenCV Tkinter PIL Pandas

Volunteer and Event Management System for NGO

(Finalists JPMC CFG) Developed a MERN-based system for volunteer and event management, with integrated data analytics, chatbot support, and email notifications.
GitHub Link

MongoDB Express.js React.js Node.js JavaScript

Privily

Created a Chrome extension to blur sensitive content during online meetings for enhanced privacy, allowing content access through user interaction.
GitHub Link

JavaScript HTML CSS Chrome Extensions API

Laptop Controller using Arduino

Developed an Arduino-based system to control laptop functions (scroll, tab switch, volume) through hand gestures, enhancing accessibility.
GitHub Link

Arduino C++ Python

Edulper NLP Suite

Developed an end-to-end NLP suite for education, featuring note-taking via speech-to-text, text summarization, FAQ-based query bot, and text-to-speech for notes. Integrated with a modern frontend for seamless user experience.
Frontend Repo | ML Backend Repo

HTML CSS JavaScript Python NLP Transformers Speech Recognition Text-to-Speech

Achievements & Recognition

JPMC Code for Good 2021

2nd Place among 16,000+ participants

Akamai EmpowerHer 2025

Top 20 Finalist (6,000+ participants)

Kotak Reign Hackathon 2022

Top 1% (50 out of 4,959 teams)

Adobe Women In Tech

National Finalist 2022

Emerging Talent Award

Providence India 2023 - Solo backend delivery in first 6 months

LeetCode

350+ Problems Solved | Striver A2Z DSA

Research Publications

📄 Fake News Detection of Live Media

IEEE Xplore - Speech-to-text based fake news detection using deep learning achieving 98%+ accuracy across multiple input formats
Publication Link

Deep Learning NLP Speech Recognition

📄 Adaptive Traffic Control System

Taylor & Francis - An adaptive traffic control system uses computer vision (YOLO) and machine learning to optimize traffic light timing in real time, reducing congestion by analyzing live traffic flow data.
Publication Link

Reinforcement Learning IoT Optimization

Let's Connect

Open to exciting opportunities in tech companies and AI-focused roles. Let's build something amazing together!

Email

dixity.2000@gmail.com

Location

Hyderabad, India

LinkedIn

Connect with me

GitHub

View my code