I'm a Computer Science student at Virtual University, but most of what I've actually learned about building software has come from client work — not the classroom. Over the past couple of years I've taken on freelance projects for businesses in the US, Canada, Denmark, and the UK, ranging from full company websites to lead-generation systems and AI-assisted content pipelines.
That real-world freelance experience is what shaped how I work: clear communication, realistic scoping, and a bias toward shipping something that actually works over something that just looks good in a pitch deck. I've built dispatch and logistics websites, set up SEO tooling access for other freelancers, scraped and structured lead data for sales teams, and handled research and virtual-assistant work for clients who needed someone they could hand a messy problem to.
Right now I'm deliberately steering that experience toward AI/ML engineering — going deeper into the systems and models behind the automations I already build, instead of just wiring tools together. The goal isn't to collect buzzwords; it's to keep being useful to clients while building toward genuinely technical, ML-driven work.