Mohammed Yasin Zuhayr

Bengaluru • India

Building reliable AI systems
and fast, impactful products.

I focus on

Full-stack & GenAI engineer. Technology Apprentice (SDE Intern) at Morgan Stanley. Former AI Trainer at xAI (Human Data). Creator of AlgoAce and PrimeEstate. I ship, measure, and iterate.

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GitHub LinkedIn Email Open to collab

LeetCode:600+ solved (top 8%)

Research:Samsung

Now:Shipping AlgoAce

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About Me

How I got here

I'm Yasin —

an engineer

and final year student from Bengaluru who's always enjoyed turning small ideas into tools people can use. That curiosity led me to study ISE at MSRIT, spend a year at xAI as an AI Trainer, conduct research with Samsung Research, and now grow as an SDE Intern at Morgan Stanley. Along the way, I've built AlgoAce (a multi-agent RAG platform for DSA learning) and PrimeEstate (end-to-end real-estate app: secure auth, listings, favorites, profiles, chat, and powerful search).

Why I build

I've always liked the feeling of making something that solves a real annoyance—first for myself, then for classmates and friends. That's still my compass: start small, make it work, and keep improving it with real feedback.

On the GenAI side, my time at xAI taught me to treat LLM features like any other system: add evaluation, tracing, and guardrails so they behave predictably. With Samsung, I learned how constraints like on-device compute shape practical recommender designs.

Milestones

Morgan Stanley · SDE Intern

xAI · AI Tutor

Samsung Research · Research Intern

Code to Give · Finalist

Creator · AlgoAce

Creator · PrimeEstate

Microsoft · Learn Student Ambassador

Cisco · Campus Ambassador

Where it started

School math contests got me hooked on problem-solving. I began with tiny web pages, then kept shipping class projects for friends who'd actually use them.

What I build

Full-stack apps with Next.js, FastAPI, and Flutter. I add realtime or GenAI when it clearly helps—like AlgoAce (multi-agent RAG for DSA).

How I work

Small iterations, quick feedback, and clear docs. I prefer tracing and simple tests over assumptions, then polish UX so things feel fast and obvious.

What I'm learning

Deepening my full-stack skills as an SDE Intern at Morgan Stanley and exploring ways to design systems that stay reliable as they scale.

City

Bengaluru

School

MSRIT · ISE

Focus

Full-stack · GenAI

LeetCode

600+ (Top ~8%)

Research

Samsung PRISM

Now

Shipping AlgoAce

Experience & Education

My journey so far

Technology Apprentice (SDE Intern)
Morgan Stanley
Aug 2025 — Present• Bengaluru · Hybrid
TypeScript
Java
React
Python
- Modernizing enterprise applications on the Application-Development track
- Full-stack delivery with CI/CD and DevOps within firm standards
AI Trainer (Coding)
LabelBox
July 2024 — Present• Remote
JavaScript
Python
Prompt Engineering
Model Evaluation
AI Trainer
xAI
Oct 2024 — Aug 2025• Remote
Python
RLHF
SFT
LLM Ops
Project Intern
Samsung Research Institute Bangalore
Aug 2024 — Jun 2025• Remote
Kotlin
Android Studio
Python
TensorFlow

Stack & tools

Technologies I use

Core toolkit across web, AI, mobile, and cloud.

Next.js

TypeScript

React

TailwindCSS

Node.js

FastAPI

Supabase

PostgreSQL

Flutter

TensorFlow Lite

Vercel

Azure

Next.js

TypeScript

React

TailwindCSS

Node.js

FastAPI

Supabase

PostgreSQL

Flutter

TensorFlow Lite

Vercel

Azure

Selected work

Projects I’ve built

AlgoAce

Multi-Agent RAG Framework for Personalized E-learning

2024 — present

Full-Stack GenAI learning platform that provides personalized learning experiences, problem recommendations, detailed explanations and personalized feedback to help users with interview preparation.

Next.jsTypeScriptReactshadcn-uiTailwindCSSFastAPIPythonSupabasePostgreSQLVercel

PrimeEstate

Real-estate marketplace with powerful search + real-time chat

2023

Full-Stack platform for property discovery with search, chat, and role-based dashboards. Strong typing and ORM for maintainable backend.

ReactJavaScriptViteTailwindCSSNode.jsExpress.jsPrismaMongoDBVercelHerokuSocket.io

IntelliCam

On-device vision with TFLite

2022

Flutter app (Mobile) that runs TensorFlow Lite models on-device for real-time object detection and classification without network latency.

FlutterDartTensorFlow

DarkGuardian Preview

DarkGuardian

Browser Extension to protect against dark patterns seen on the internet.

2021

A Browser Extension to protect against dark patterns seen on the internet. Utilises a Flask App and chrome extension to detect dark patterns in e-commerce websites. Scrapes Data using Beautiful Soup 4 and processes the data using the fine-tuned BERT and LLAMA models to provide accurate results. Lightweight and auditable.

ReactTypeScriptFlaskPython

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Custom development, MVP builds, or technical consulting