Available for opportunities

Md Zahin
Uddin

Senior Software Engineer with 3+ years at Samsung R&D. Specializing in scalable full-stack systems, AI/ML integration, and performance optimization. Currently pursuing M.Sc. CS at Memorial University.

3+
Years at Samsung
15%
Perf. Improvement
40+
Teams Beaten
95%
ML Accuracy
Md Zahin Uddin - Software Engineer
Open to Work · St. John's, NL
About Me

Engineered for
High Performance

I'm a results-driven Software Engineer with a track record of building production-ready, scalable systems. My 3+ years at Samsung R&D Institute Bangladesh sharpened my skills in front-end architecture, AI/ML integration, and cross-platform development including iOS.

Currently deepening my research chops through an M.Sc. in Computer Science at Memorial University of Newfoundland, where I recently won the Fastest BFS Search Code award in graduate-level competition.

I bring a rare mix of industry engineering experience and academic rigor — fluent in English (IELTS Band 7), and passionate about building software that genuinely moves the needle.

Technical Skills

Languages

Python JavaScript Java C/C++ Swift SQL

Frontend

React.js Next.js HTML/CSS UIKit

Backend

Node.js Spring Boot RESTful API MongoDB

Tools & Cloud

Git/GitHub GCP Cloudinary VS Code IntelliJ

AI / ML

XGBoost ANN Scikit-learn Jupyter

Other

Stripe Clerk iOS Dev LaTeX
Work Experience

Where I've Worked

3+ years of industry engineering across enterprise and startup environments.

Samsung R&D Institute Bangladesh
Senior Software Engineer
📍 Dhaka, Bangladesh
Nov 2022 – Dec 2025
  • Led front-end development using React.js for enterprise-scale applications
  • Improved application performance by 15% through code optimization and architecture refactoring
  • Built full-stack features using JavaScript, Node.js, and Python
  • Integrated AI/ML capabilities into production web applications
  • Contributed to iOS development for Samsung SmartThings (Swift, UIKit)
  • Led research initiatives contributing to patents and innovation
JavaScript React.js Node.js Java Python Swift UIKit
Tudo Technologies Pvt. Ltd.
Junior Software Developer
📍 Bengaluru, India (Remote)
Dec 2021 – Nov 2022
  • Led React.js front-end development and built backend services with Node.js
  • Mentored 3 junior developers and delivered multiple production projects
  • Integrated Google APIs to enhance platform functionality
HTML/CSS JavaScript React.js Node.js
Featured Work

Projects

Production-grade software — from AI SaaS to algorithmic solutions.

🖼️
ModifyMate
AI-powered SaaS web app for advanced image modification. Features restoration, recoloring, generative fill, object removal, and semantic search.
Next.js MongoDB Cloudinary AI Stripe Clerk
View details →
🤖
SmartThings iOS Integration
Contributed to Samsung SmartThings iOS development, building native features with Swift and UIKit for millions of Samsung ecosystem users.
Swift UIKit iOS Samsung
View details →
🧬
Cardiovascular Prediction Model
Undergraduate research using XGBoost with correlation-based feature selection achieving 95.06% accuracy in cardiovascular breakdown prediction.
Python XGBoost ANN ML
View details →
Education

Academic Background

Strong foundation across theory, algorithms, and applied systems.

M.Sc. in Computer Science
Memorial University of Newfoundland
📅 January 2026 – Present
📍 St. John's, NL, Canada
B.Sc. in Computer Science & Engineering
University of Chittagong
📅 January 2017 – August 2022
CGPA: 3.45 / 4.00
Recognition

Achievements

Awards from competitions, certifications, and academic excellence.

🏆
BUET CSE Fest Hackathon 2022
Best Documentation Award — Team Scapegoat. Outperformed 40+ competing teams. Prize: 15,000 BDT.
Fastest BFS Search Code — MUN 2026
Awarded fastest BFS implementation among all graduate students in CS 6980 at Memorial University.
🎓
Samsung SW Professional Certificate
Excellence in SW Certificate Test (SWC00631). Internal Capability Certification — Samsung Electronics, Nov 2023.
🥇
CUET Programming Contest 2019
Ranked 11th out of numerous participating teams in competitive programming contest.
Research

Undergraduate Research

Undergraduate Thesis
Evaluating Features Impact on Cardiovascular Breakdown Prediction
Using ANN and Machine Learning Models
Supervisor
Prof. Dr. Kazi Ashrafuzzaman
Method
Correlation-based feature selection
Best Accuracy
XGBoost — 95.06%
Models Used
XGBoost, ANN, ML Ensemble
Let's Connect

Open to New
Opportunities

Whether you're a recruiter, collaborator, or just want to chat about tech — I'd love to hear from you.