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Muhammad Hussnain

@muhammadhussnain

Data scientist and Machine learning engineer with hands on experience designing, training, and deploying production-grade ML systems

Pakistan

Message

What I'm looking for

A position that allows me to put my knowledge and skills in Data Science, Machine Learning, and AI into practice while making a difference through problem-solving and developing solutions is what I am searching for. I find it rewarding to tackle tough challenges, and take an active part in all aspects of building machine learning solutions, from creating models to deployment.

Data Scientist & Machine Learning Engineer building end-to-end AI solutions that ship to production not just notebooks.

I design, train, and deploy machine learning, deep learning, computer vision, and NLP systems that solve real business problems. My work spans fraud and malware detection, fake-news classification with BERT-based models, time-series forecasting, recommendation systems, and computer vision. I'm also hands-on with generative AI LLM fine-tuning (PEFT/LoRA) and RAG pipelines (LangChain, Chroma) and I'm currently building MSAF-TomNet, a novel deep-learning architecture for plant-disease detection.

Technical skills: Python, SQL · PyTorch, TensorFlow, scikit-learn, pandas, NumPy · Hugging Face Transformers (NLP) · LangChain · AWS & GCP · Docker, MLflow, and MLOps for production deployment.

What drives me is turning the latest AI into measurable results for businesses — owning problems from concept through deployment and seeing the real-world impact of what I build.

Experience

Work history, roles, and key accomplishments

Machine Learning Engineer

ARK Innovision

May 2025 - May 2026 (1 year)

Designed and deployed end-to-end ML models for classification, prediction, and automation across client domains. Built scalable pipelines ingestion, preprocessing, training, and CI-driven deployment shipped on GCP and AWS via REST APIs. Developed MSAF-TomNet, a novel multi-scale attention CNN reaching 97.5% accuracy at <50ms inference, faster than previous baselines.

Deep Learning Machine Learning MLOps Google Cloud Platform AWS CI CD Pipelines Data Analysis Model Training Model Evaluation

Data Scientist

NBThub

Feb 2024 - Apr 2025 (1 year 2 months)

Partnered with cross-functional teams to deliver ML and data-driven solutions powering business analytics. Owned data cleaning, preprocessing, feature selection, and EDA on complex datasets, streamlining analysis pipelines for better results in less time. Built a brain-tumor classifier (U-Net + VGG16) reaching 95% accuracy via segmentation-guided learning.