I'm a passionate Machine Learning Engineer with 1+ years of experience building ML models, scalable AI solutions, and backend systems. I have a strong foundation in Data Science, MLOps, and Full-Stack Development, seeking opportunities in AI/ML Engineering and Applied Data Science.
- 🧠 Expertise in Python, C++, JavaScript, Golang, ML Frameworks, DL, & LLMs.
- 💻 Skilled in Full-Stack Development and Agile Methodologies.
- ☁️ Experienced with MLOps, DevOps, and Cloud Platforms.
- 🔭 Working on ML models for DaaS & ETL pipelines with Snowflake/Flask.
- 🌱 Learning advanced ML techniques and MLOps practices.
- 🤝 Looking to collaborate on challenging SaaS and ML/AI projects.
- 💬 Ask me about Machine Learning, Deep Learning, Data Science, or MLOps.
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Developed a custom CNN to classify MRI images from the OASIS dataset into four dementia stages, achieving 99.99% accuracy.
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Built a deep learning model using EfficientNet with advanced data augmentation and hyperparameter tuning to classify MRI scans with 99.5% accuracy.
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Developed a cancer drug sensitivity predictor (R²=99.41%) with XGBoost for IC50 predictions, integrating SHAP for interpretability.
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Built a cardiovascular disease risk predictor using XGBoost (73.66% accuracy, 0.75 precision, 0.69 recall), leveraging key health indicators. Integrated SHAP for explainability.
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