Emilcan Arıcan

I am a senior software engineer focused on building scalable, cost‑effective machine learning and cloud infrastructure that enables scientific and production workloads. I design orchestration systems, CI/CD pipelines, and tooling to reduce deployment friction and improve reliability.

At Microsoft Research I built systems to fine‑tune and serve models asynchronously on low‑priority Azure VMs, implemented graceful shutdown and large‑scale orchestration up to 50,000 nodes, and automated weekly Docker rebuilds across many projects to maintain security and currency.

Previously I delivered real‑time data pipelines and trading automation using AWS and Airflow, and implemented backend and CI/CD solutions as a software engineer and quant developer. I have research experience in NLU, reproducing academic results and building data transformation tooling for training.

I combine strong engineering discipline with practical research and quantitative experience, emphasizing code quality, tooling, and reproducible systems to drive measurable improvements in performance, security, and developer productivity.