AI / Machine Learning Engineer | Software Developer | Data-Driven Problem Solver
Designing intelligent systems, writing production-quality code, and turning complex data into actionable solutions.
I am a software developer with a strong specialization in Artificial Intelligence and Machine Learning, focused on building end-to-end, real-world systems rather than isolated experiments.
My GitHub reflects:
- Practical AI/ML pipelines
- Strong software engineering fundamentals
- Emphasis on clarity, reproducibility, and scalability
- Projects aligned with industry and research use-cases
I aim to contribute to teams working on applied AI, data-centric products, and scalable systems.
- Supervised & unsupervised learning
- Model training, evaluation, and optimization
- Feature engineering & data preprocessing
- Applied ML for real-world datasets
- Modular, maintainable Python codebases
- Clear project structure & documentation
- Algorithmic problem-solving
- Performance-aware implementation
- Data cleaning and transformation
- Exploratory Data Analysis (EDA)
- Statistical reasoning
- Visualization for insights and validation
- Python (primary)
- C / C++
- Java
- SQL
- Scikit-learn
- TensorFlow / PyTorch
- NumPy, Pandas
- Matplotlib, Seaborn
- Git & GitHub
- Linux
- Jupyter Notebook
- Virtual environments & dependency management
✔️ End-to-end AI / ML projects
✔️ Data preprocessing and feature engineering pipelines
✔️ Model training & evaluation workflows
✔️ Clean, well-documented Python code
✔️ Learning-driven projects with practical outcomes
Each repository is structured to be:
- Easy to understand
- Easy to reproduce
- Easy to evaluate by recruiters and engineers
I am actively preparing for roles such as:
- AI / Machine Learning Engineer
- Software Engineer (AI-focused)
- Data Scientist
- Applied ML / Research Engineer
I am particularly interested in:
- Applied AI systems
- Computer Vision