AI, software, and data—treated as one engineering system.

My work sits at the intersection of model development, reliable data, and the software required to make intelligent systems useful. I have built computer-vision pipelines with CNNs and Vision Transformers, worked across Keras and PyTorch, and supported production data engineering workflows.

Engineering direction

I’m moving beyond isolated model experiments toward complete AI applications: data preparation, training and evaluation, retrieval, agents, APIs, and deployment. The goal is to build systems that are technically sound and operationally useful.

Current learning

I am completing the IBM AI Engineering Professional Certificate while extending my foundation in deep learning into Generative AI, LLM applications, RAG, agentic workflows, and production AI engineering.

Career focus

I’m targeting early-career AI/ML Engineering, AI Engineering, Machine Learning, Data Science, and Generative AI roles where strong computer science fundamentals and hands-on systems work matter.