About Muhammad Adnan
Machine Learning Engineer and Data Professional with a Ph.D. in Computational Mathematics, specializing in data pipelines, applied machine learning, and AI-driven solutions.
I help companies transform raw and unstructured data into actionable insights and scalable systems. My experience includes building end-to-end data workflows, from data ingestion and cleaning to analysis and deployment. I have developed Retrieval-Augmented Generation (RAG) pipelines for document processing and semantic search, enabling efficient information retrieval from complex datasets.
My core expertise includes Python (Pandas, NumPy, Scikit-learn), SQL, ETL pipeline development, and data transformation. I also work with data visualization tools such as Power BI and Excel to deliver clear, decision-ready outputs.
I focus on delivering practical, business-oriented solutions, including:
- Data cleaning and structuring for reliable analytics
- Dashboard development and reporting
- Machine learning models for pattern detection and prediction
- AI-powered document and knowledge systems (RAG)
- Automated data pipelines and workflows
I am comfortable working with both structured and unstructured data and collaborating with cross-functional teams. I prioritize clarity, reliability, and scalability in every project.
Available for freelance projects in data analysis, machine learning, and AI system development.
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- AIcloudersMachine Learning EngineerApril 2024 - Today (2 years and 2 months)• • Designed and implemented a Retrieval-Augmented Generation (RAG) system for document-based question answering• • Built full pipeline: document ingestion → preprocessing → chunking → embedding generation → retrieval → response generation• • Implemented FAISS-based vector search for semantic retrieval over unstructured documents• • Developed REST-style interaction layer using FastAPI concepts and modular architecture• • Built interactive UI using Streamlit for real-time querying• • Optimized retrieval quality using embedding tuning and prompt engineering Document Retrieval & QA System• • Developed AI system for querying domain-specific documents using embeddings and vector search• • Implemented preprocessing pipelines for structured and unstructured data (PDF/JSON)• • Built automated workflows for data ingestion and retrieval• • Focused on improving grounding and reducing hallucinations in LLM responses Vector• • Built machine learning models to predict customer behavior and improve engagement• • Developed ETL pipelines for data cleaning, feature engineering, and model training• • Integrated models into a reproducible workflow for analysis and deployment• • Collaborated within a team to deliver a complete AI-driven solution• • Developed ML models using PyTorch for high-dimensional scientific datasets• • Processed large-scale structured data and extracted meaningful patterns• • Combined domain knowledge with machine learning for predictive modeling Built real-time object detection and tracking system OpenCV Implemented video stream processing pipeline for live inference Developed interactive Python-based interface for visualization and control
- Personal TutorData Science InstructorJanuary 2022 - December 2023 (1 year and 11 months)• • Delivered training on Python, ML, and AI concepts• • Designed hands-on projects involving real-world datasets• • Mentored students on ML workflows and best practices
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Education
- Ph.D. in Computational MathematicsLahore University of Management Sciences (LUMS)2022Ph.D. in Computational Mathematics
- M.Phil. inUniversity of Engineering and Technology2018M.Phil. in
Certifications
- PythonData Science with Python2022