Vin̆it Üpadhy̆åy̆
Creating with code. Small details matter.
Overview
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About
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.
Let's connect and collaborate!
Current Work
QuickTube
QuickTube is a collaborative workspace for YouTube creators and their editing teams. The app brings channel management, video review, editor handoff, metadata prep, and publishing support into one shared workflow instead of spreading work across downloads, chat threads, and spreadsheets.
Stack
Experience
Outlier
Current Employer- Worked on rubric-based RLHF projects where I wrote detailed system prompts to guide model responses and evaluated how well the LLM performed.
- Reviewed AI-generated frontend outputs, especially landing pages and dynamic web interfaces, checking for functionality, responsiveness, code quality, and visual accuracy.
- Collaborated with senior research teams and domain experts, aligning evaluation criteria with industry-quality benchmarks to advance enterprise-grade AI models.
- 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(3)
MindMarket Landing Page — Technical Study
Femworld — Luxury Fashion E-commerce
Quicktube
Certifications(4)
Vin̆it Üpadhy̆åy̆
Frontend Engineer