Programming Languages
I have several years of experience developing machine learning and data-driven systems using Python for experimentation, modeling, and end-to-end pipelines. I complement this with a working knowledge of C++, experience in R and MATLAB for statistical analysis and signal processing, and practical use of SQL for managing and querying structured data.
Machine Learning Frameworks
I have extensive expertise in PyTorch and TensorFlow, using them to design, train, and optimize deep learning models in practice. I also work regularly with scikit-learn for classical machine learning and evaluation, and have strong experience with ONNX for exporting, optimizing, and deploying models across different frameworks and runtime environments.
MLOps & AI Tools
I have solid experience with modern MLOps and AI tooling, with a particular focus on working with Hugging Face and large language models for fine-tuning, evaluation, and deployment. I use Git for version control and collaboration, MLflow for experiment tracking and model management, and have practical experience deploying and running models locally using Ollama, alongside cloud-based workflows supported by Microsoft Azure.
Data Analysis & Visualization
I work extensively with pandas to prepare, organize, and analyze data as a foundation for modeling and decision-making. Using Matplotlib and Seaborn, I design visualizations that reveal patterns, validate assumptions, and communicate insights in a clear and professional manner.