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Muhammad Usman

ML Engineer + AI Engineer, Data Scientist, Python Developer, and Frontend Developer

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Automated Grading & Learning Analytics

Intelligent automated grading system using rule-based logic and data analytics to evaluate student performance, reduce manual grading effort, and provide learning insights.

Automated Grading Platform screenshot
Intelligent Document Summarizer screenshot

Intelligent Document Summarizer API

AI-powered REST API that summarizes PDF/DOCX/TXT documents, extracts keywords, and answers natural language questions using Groq LLaMA 3.3 70B with offline fallback.

Predicting Students Career Aspirations

ML models predicting students' career aspirations from academic and personal data. Random Forest classifier with 80% accuracy, deployed via FastAPI with career recommendations.

Career Aspiration Predictor screenshot
PrimeBrothers Store screenshot

PrimeBrothers E-Commerce Platform

Full-stack e-commerce solution with React frontend, Node.js backend, and PayFast payment integration for a seamless online shopping experience.

Experience

July 2025 – September 2025Data Science Track

Data Science Intern

ITSOLERA PVT LTDJuly 2025 – September 2025

Developed end-to-end data science solutions including exploratory data analysis, feature engineering, and model building. Built predictive models for disease diagnosis and financial risk forecasting. Deployed models as production APIs using FastAPI and Flask, and created interactive dashboards in Streamlit to communicate insights to non-technical stakeholders.

Scikit-learnPandasFastAPIFlaskStreamlitEDAPython

Certificate of Completion

Data Science Internship Certificate — ITSOLERA PVT LTD
February 2025 – July 2025Machine Learning Track

Machine Learning Intern

ITSOLERA PVT LTDFebruary 2025 – July 2025

Built supervised and unsupervised ML models for real-world datasets including sentiment analysis (NLP), anomaly detection in time-series data, and multi-class classification. Worked across the full pipeline — data cleaning, feature selection, model training, evaluation, and API deployment — building a strong foundation in applied machine learning.

Scikit-learnNLPSentiment AnalysisAnomaly DetectionFastAPIPython

Certificate of Completion

Machine Learning Internship Certificate — ITSOLERA PVT LTD
July 2024 – October 2024Deep Learning Track

Artificial Intelligence Intern

ITSOLERA PVT LTDJuly 2024 – October 2024

Contributed to four team-based deep learning projects — an AI-Powered Interactive Learning Platform, a Super-Resolution Imaging system, an Augmented Reality Try-On experience, and a Smart Parking System with real-time space detection. My focus across all four was building robust data collection and preprocessing pipelines that fed directly into model training workflows.

Deep LearningPyTorchOpenCVData PipelinesYOLOPython

Certificate of Completion

Artificial Intelligence Internship Certificate — ITSOLERA PVT LTD

Hi there

I'm Muhammad Usman — a fresh Machine Learning Engineer and AI Engineer who graduated with a Bachelor of Science in Computer Science from the University of Sindh, Jamshoro in February 2026. During my degree and three back-to-back internships at ITSOLERA PVT LTD, I gained hands-on experience designing, training, and deploying intelligent systems — from classical ML pipelines to deep learning models and LLM-powered applications. Take a look at the tools I work with on my uses page.

Core stack: Python is my primary language across the full ML lifecycle. I build and train models with Scikit-learn, TensorFlow / Keras, and PyTorch, serve them as REST APIs using FastAPI and Flask, and package everything with Docker. For data analysis and visualisation I rely on Pandas, NumPy, Matplotlib, Seaborn, and Plotly. I track experiments with MLflow, manage environments with Conda, and keep all work version-controlled with Git. I am actively expanding my cloud skills on AWS (EC2, S3, Lambda, SageMaker).

What I specialise in: Supervised & unsupervised learning, Natural Language Processing, Computer Vision, Time-Series forecasting, end-to-end MLOps pipelines, and REST API development for ML products. I enjoy bridging the gap between research-quality models and production-ready systems that genuinely help people.

Currently learning: Fine-tuning Large Language Models with HuggingFace PEFT / LoRA, building Retrieval-Augmented Generation (RAG) pipelines with FAISS and Pinecone, and integrating LLM APIs (Gemini, Groq) into real applications. On the infrastructure side I am deepening my knowledge of AWS SageMaker for managed training and deployment, setting up CI/CD pipelines for ML with GitHub Actions and Docker Compose, and exploring real-time Computer Vision with YOLO and OpenCV.

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