News Summarization AI
Deep learning news summarizer achieving ROUGE-1: 71.43% and BERTScore: 0.93 using PRIMERA & LED architecture.
AI & Machine Learning Engineer
Hi, I’m Mohd. Musheer.
AI & Machine Learning Engineer building high-performance, production-grade ML systems.
I specialize in systems-level machine learning, high-performance C++ development, transformer-based NLP, and scalable AI deployment. I build frameworks, optimize performance, and ship real-world AI systems — not just experiments.
Creator of VectorForgeML — a C++ ML framework powered by BLAS/LAPACK and OpenMP.
About Me
Machine Learning Engineer focused on systems-level ML
I'm a Machine Learning Engineer who builds production-grade ML systems from the ground up. My flagship project, VectorForgeML, is a complete ML framework written from scratch in C++ — featuring BLAS/LAPACK hardware acceleration, OpenMP parallelism, and zero-copy R integration.
With 25+ ML/AI projects spanning NLP, Computer Vision, and Predictive Analytics, I focus on the intersection of systems architecture and machine learning — writing code that's not just accurate, but fast, scalable, and deployment-ready.
Currently pursuing my BCA at Sant Gadge Baba Amravati University, I've already completed an ML internship at Future Interns and authored research on production ML framework design.
25+
ML/AI Projects
9+
Algorithms from Scratch
1
ML Framework Built
1
Research Paper
Education
Bachelor of Computer Applications (BCA)
Sant Gadge Baba Amravati University, Maharashtra, India
Expected: May 2026
Technical Skills
Core technologies and tools I work with
Languages
ML / AI
Frameworks & Tools
Cloud & DevOps
Data Science
Projects
Highlights from 25+ ML/AI projects
Flagship Project
VectorForgeML
Production-grade ML framework built from scratch in C++
A next-generation machine learning framework bridging R's simplicity with C++'s raw performance. Features 9+ algorithms, BLAS/LAPACK hardware acceleration, OpenMP parallelism, and zero-copy R integration via Rcpp.
9+
Algorithms
C++/R
Languages
BLAS
HW Accelerated
Zero-Copy
R Bridge
AI Resume Ranking System
AI-powered resume screening system processing 1000+ resumes using TF-IDF vectorization for candidate-job matching.
Employee Attrition Predictor
End-to-end ML pipeline for predicting employee attrition with feature engineering and API-ready architecture.
YouTube Sentiment Analysis
AI-powered YouTube comment analysis for mental health profiling using NLP sentiment patterns.
Support Ticket Classifier
NLP-based support ticket classification and prioritization using TF-IDF and ensemble ML models.
CIFAR-10 Image Classifier
CNN-based image classification built from scratch in PyTorch with data augmentation strategies.
Breast Cancer Predictor
Medical ML model achieving 98%+ diagnostic accuracy using PyTorch binary classification.
T5 News Summarization
T5-small fine-tuning for abstractive news summarization with ROUGE evaluation metrics.
Email Spam Detector
End-to-end NLP spam detection pipeline for email and SMS using binary classification.
Experience
Professional internship and training
Machine Learning Intern
Future Interns
Completed an intensive ML internship building production-grade machine learning systems. Worked on real-world datasets spanning sales forecasting, NLP classification, and AI-powered recruitment tools.
Letter of Recommendation
Certificate of Completion
CIN: FIT/JAN26/ML4913
AI Resume Ranking System
Built an AI-powered resume screening system processing 1000+ resumes using TF-IDF vectorization for candidate-job matching and skill gap analysis.
Support Ticket Classifier
Developed an NLP-based support ticket classification and prioritization system using TF-IDF and ensemble ML models.
Sales Demand Forecasting
Created a sales and demand forecasting model using Random Forest Regressor on real-world sales data.
Research
Published academic work
VectorForgeML: A Production-Grade Machine Learning Framework in C++
This paper presents VectorForgeML, a modular machine learning framework built entirely from scratch in C++ with R bindings. The framework implements 9+ supervised and unsupervised algorithms including Linear Regression, Logistic Regression, Ridge Regression, Softmax Regression, Decision Trees, Random Forests, KNN, PCA, and K-Means Clustering. Key architectural decisions include BLAS/LAPACK integration for hardware-accelerated linear algebra, OpenMP for multi-core parallelism, and zero-copy data exchange between R and C++ via Rcpp.
Key Findings
- Raw C++ pointers enable efficient graph-based models (Decision Trees, Random Forests)
- BLAS/LAPACK integration provides hardware-accelerated matrix operations
- OpenMP parallelism enables multi-core training for ensemble methods
- Zero-copy Rcpp bridge eliminates data transfer overhead between R and C++
- Modular pipeline architecture supports complex ML workflows
C++
Machine Learning
BLAS/LAPACK
OpenMP
R Package
Zero-Copy
Certifications
Professional credentials and coursework
Machine Learning Internship Completion
Future Interns
Successfully completed ML internship covering sales forecasting, NLP classification, and AI resume ranking.
CIN: FIT/JAN26/ML4913Artificial Intelligence
University Curriculum
Comprehensive AI coursework covering machine learning algorithms, neural networks, and AI system design.
Business Intelligence
University Curriculum
Business Intelligence and Analytics coursework covering data visualization, dashboard design, and decision support systems.
Get in Touch
Interested in working together? Let's connect.
Send an Email
Amravati, Maharashtra, India
musheerayan@gmail.com
Languages: Hindi (Native) / Urdu (Fluent) / Marathi (Fluent) / English (Professional)