Hello, World! I am Vinit Upadhyay — a Front-End Developer passionate about creating high-performance, user-centric software solutions with intuitive and engaging designs.
Currently working as an AI Trainer & Reviewer at Outlier, where I collaborate with top AI organizations to enhance LLM through expert-level front-end development insights. I contribute to the training of generative AI by creating and answering questions related to web development, evaluating AI-generated code, and reviewing UI/UX quality.
Previously, I worked as an SDE (Frontend Engineer) at SameSpace, where I engineered UI components for the Wave analytics platform, resulting in 20% faster page loads and 15% higher user engagement. I optimized frontend with Tanstack Query & GraphQL, reducing API call overhead by 35% and data transfer by 40%.
I specialize in modern front-end technologies including React.js, Next.js, TypeScript, and Tailwind CSS, with a strong focus on responsive design, accessibility (WCAG-compliant), and best UX practices. I'm also proficient in backend technologies like Firebase, Express.js, and databases like MySQL and MongoDB.
One of my key projects, QuickTube, is a platform streamlining video review and approval between YouTubers and editors, reducing the review process time by 40%. It integrates seamless YouTube channel connectivity, editor access to workspaces, and a notification system via WhatsApp or Slack.
I'm currently pursuing a BS in Data Science and Application at IIT Madras, and hold a BSc in Computer Science from SIES College of Arts, Science, and Commerce.
Collaborating with top AI organizations to enhance LLM through expert-level front-end development insights.
Contributing to the training of generative AI by creating & answering questions related to web development, evaluating AI-generated code, and reviewing UI/UX quality.
Specializing in modern front-end technologies including HTML, CSS, JavaScript, React, TypeScript and Next.js, with a strong focus on responsive design, accessibility, and best UX practices.
Providing critical feedback on AI outputs to improve design accuracy, interaction patterns, & overall user interface quality.
React
TypeScript
Next.js
HTML
CSS
JavaScript
UI/UX Design
Accessibility
AI Training
Code Review
SameSpace
Engineered UI components for Wave analytics platform, resulting in 20% faster page loads and 15% higher user engagement.
Optimized frontend with Tanstack Query & GraphQL, reducing API call overhead by 35% and data transfer by 40%.
Developed 15+ reusable, accessible (WCAG-compliant) UI components, accelerating delivery across 8 product modules by 25%.
Monitored frontend performance using browser dev tools, Lighthouse, and custom metrics logging; improved time-to-interactive (TTI) by 22%.
React
TypeScript
Tanstack Query
GraphQL
WCAG
Performance Optimization
Lighthouse
UI Components
Analytics
Education
Currently studying for a BS in Data Science and Application.
Located in Chennai, India.
Data Science
Statistics
Machine Learning
Python
R
SQL
Personal Projects(2)
Developed a modern luxury fashion e-commerce platform using Next.js 15, React 19, and TypeScript, featuring responsive design with Tailwind CSS and Framer Motion animations.
Implemented GraphQL API with Prisma ORM and PostgreSQL database, achieving 40% faster data fetching compared to REST APIs and reducing database query overhead by 35%.
Built comprehensive e-commerce features including product catalog, shopping cart, user authentication, wishlist functionality, and advanced search with filtering capabilities.
Integrated Supabase backend services, implemented Row Level Security (RLS), and developed admin dashboard for product and collection management, improving operational efficiency by 30%.
Optimized performance with React Query caching, implemented accessibility features (WCAG-compliant), and utilized modern development practices including Docker containerization and automated testing.
Next.js 15
React 19
TypeScript
Tailwind CSS
Framer Motion
GraphQL
Prisma ORM
PostgreSQL
Supabase
Row Level Security
React Query
Docker
WCAG
Spearheaded a team to develop QuickTube, a platform streamlining video review and approval between YouTubers and editors, reducing the review process time by 40%.
Integrated seamless YouTube channel connectivity, editor access to workspaces, and a notification system via WhatsApp or Slack, improving collaboration efficiency by 30%.
Facilitated video metadata customization, a two-step approval process, and enhanced security for content before YouTube upload, reducing content errors by 20%.
Leveraged React.js, Node.js, Express, Firebase, YouTube API, Twilio API, and Slack API in the technology stack, ensuring scalability and performance.
React.js
Node.js
Express
Firebase
YouTube API
Twilio API
Slack API
Real-time Collaboration
Video Review
Client Projects(4)
Built a professional project estimation tool with Next.js 15 (React 19, TypeScript) featuring feature toggles and per-feature complexity sliders.