I'm a software developer and DevOps engineer based in Wormer, the Netherlands. I design, develop, and maintain cloud-based software systems with a focus on reliability, maintainability, and scalability. I prefer automation over manual processes and value clean code, reproducibility, and pragmatic solutions over complexity.
Day to day I work across the full stack — from backend services in Go and Python to AWS cloud infrastructure and CI/CD pipelines. I'm particularly interested in serverless architecture, infrastructure as code, and developer productivity tooling. AI-assisted development has become a core part of my workflow — I use GitHub Copilot at work and Claude Code for personal projects. It has fundamentally changed how I build software, and I'm always looking for new ways to integrate AI into my development process.
Before moving into software development, I completed a Master's in Data Science at the University of Amsterdam. My thesis research resulted in PIE: Pseudo-Invertible Encoder, a paper co-authored with Ivan Sosnovik and Arnold Smeulders and submitted to ICLR 2019. That academic background gave me a strong foundation in problem-solving and analytical thinking that I apply every day in my engineering work.
Outside of tech, some people may know me from a brief stint making music — I wrote a couple of Dutch protest songs against the student loan system that got some attention back in the day. That chapter is behind me, but the videos are still on YouTube.
Plinkr
Full-stack development and DevOps across multiple products. Building and maintaining cloud-based applications in Go and Python, designing serverless AWS infrastructure, and automating deployment pipelines with GitHub Actions. Cross-platform mobile development with Flutter. Responsible for platform reliability and developer tooling.
Primed IO
Applied machine learning and data engineering for real-time bidding and ad-tech optimization. Built data pipelines and predictive models to improve bidding strategies and campaign performance.
University of Amsterdam
Thesis research on pseudo-invertible encoders for likelihood-based autoencoders, resulting in a paper submitted to ICLR 2019 (co-authored with Ivan Sosnovik and Arnold Smeulders).