Mathematics & Artificial Intelligence student working on LLM training, inference systems, and GPU/performance engineering.

My focus is on the engineering layer behind AI systems: training runs, inference performance, CUDA/C++, backend infrastructure, and reliable tooling.

• LLM training and inference systems
• CUDA and performance-oriented C++
• Backend infrastructure in Go and Python
• Reproducible experiments and technical benchmarking
• Systems-level software design

Languages: Python, Go, C++, CUDA, TypeScript, SQL
Systems: PyTorch, CUDA, Linux, PostgreSQL, ONNX Runtime, FAISS, Git

I am currently building stronger public work around LLM infrastructure, GPU programming, and performance-oriented AI systems.