MD Kaif Sardar

Full-Stack Engineer & B.Tech Candidate (KGEC '27). Building scalable, secure applications with a focus on clean APIs and system design. Tech-curious and ready to tackle real-world challenges in AI/ML and Cloud.
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Full Stack Engineering

System Architecture

Applied AI & Cloud

About

A quick tour through the way I build

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Dashboards and trading UIs stay sub-second, even with real-time data.
Fast product surfaces
OpenAPI specs, RBAC, and Azure secrets keep every endpoint auditable.
Secure REST APIs
Eager to Learn and Adapt
ReactJSExpressTypescript
VueJSNuxtJSGraphQL
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Deploy on Vercel + Azure with telemetry, error budgets, and rollback playbooks.
Cloud-aware delivery
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Type-safe, tested, and peer-reviewed codebases
Production ready code
Student builder

Achievements

Impact Measurements

6+ ShippedCareer Output

Freelance & Enterprise Projects

Delivered end-to-end full-stack platforms for education, trading, and analytics clients, maintaining strict SLAs.

10K+ UsersGlobal Impact

Cumulative Client Reach

Active daily users across deployed platforms like Stitch My Clothes, EduTouch and JeoNFT, scaling horizontally without friction.

99.9% UptimePerformance

System Reliability

Architecture designed for fault tolerance and high availability, ensuring mission-critical exams and trades never fail.

Certifications

2024

Supervised Machine Learning: Regression and Classification

DeepLearning.AI & Stanford Online (Coursera)

Andrew Ng specialization track covering linear regression, logistic regression, and regularization best practices.

2025

Advanced Learning Algorithms

DeepLearning.AI & Stanford Online (Coursera)

Neural networks, decision trees, and optimization techniques guided by Andrew Ng's ML Specialization.

2025

Unsupervised Learning, Recommenders, and Reinforcement Learning

DeepLearning.AI & Stanford Online (Coursera)

Clustering, anomaly detection, recommender pipelines, and RL foundations from the Andrew Ng-led series.

2025

Neural Networks and Deep Learning

DeepLearning.AI & Stanford Online (Coursera)

Build foundational deep learning models, understand neural network architecture, and apply deep learning to real-world problems.

A small selection of recent projects

My work experience