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@shuser1

AI Developer and Blockchain Developer building MERN, REST APIs, and Web3 DApps.

Zimbabwe
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What I'm looking for

I want to build secure AI and Web3 applications end-to-end—using ML/NLP, REST APIs, and smart contracts—while collaborating with teams that value problem solving, delivery focus, and continuous learning.

I’m an AI Developer and Blockchain Developer focused on building real-world, database-driven applications and Web3 experiences. I combine strong foundations in DSA, OOP, and SDLC with hands-on work across Python, Java, and JavaScript.

As an AI Developer intern at Dotcom infoway (march 2026-current), I develop machine learning models for classification, regression, and clustering using Python and Scikit. I perform data preprocessing (missing value handling, feature encoding, normalization), then train and evaluate models such as Logistic Regression, Decision Trees, Random Forest, SVM, KNN, and Naive Bayes with cross-validation, accuracy checks, and performance tuning.

I also build full-stack and blockchain solutions through projects like my Blockchain Voting DApps. Using Solidity, React.js, Web3.js, and Ethereum, I created decentralized voting with smart contracts for voter registration and result computation, integrating Web3.js with MetaMask for secure authentication.

On the AI side, I build NLP-powered products like my AI Job Chat-bot with Python and Flask REST APIs. I implement intent classification to improve response accuracy and reduce repetitive manual support queries, and I create secure, real-time web experiences with MERN, OTP-based login, JWT authentication, and Socket.io for low-latency messaging.

Experience

Work history, roles, and key accomplishments

DI
Current

AI Developer Intern

Dotcom Infoway

Mar 2026 - Present (1 month)

Developed machine learning models for classification, regression, and clustering using Python and scikit-learn. Performed data preprocessing (missing value handling, feature encoding, normalization), trained models with algorithms such as logistic regression, decision trees, random forest, SVM, k-NN, and Naive Bayes, and evaluated results with cross-validation and performance tuning.

Education

Degrees, certifications, and relevant coursework

Alagappa University logoAU

Alagappa University

Master of Science, Information Technology

Grade: CGPA: 8.3/10

Completed an M.Sc in Information Technology at Alagappa University.

FC

Fatima College

Bachelor of Science, Information Technology

Grade: Percentage: 70%

Completed a B.Sc in Information Technology at Fatima College.

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