The languages, frameworks, and tools I reach for, and the projects and roles where I have actually put them to work.
I learned most of this the same way: pick a real problem, ship something, and keep the parts that survive contact with users. So rather than a wall of logos, each skill below comes with the projects, jobs, and studies that built it.
Proficiency reflects how confidently I can take something from idea to production, not just whether I have touched it once.
Python is where I first taught myself to code in school. It's still my quickest path from idea to a shipped product, whether that's an ML experiment, a production API, or a small automation script.
Java started as a school assignment and never left my toolbox. I taught it to first-years at TUM, ship backend services with modern JVM tooling, and use it in my work environment.
At Westend61 I look after Groovy/Grails services that power internal APIs, services and automation. The JVM roots keep everything familiar while Groovy's scripting side lets me land integration fixes and admin tools fast.
I picked up Swift to build NeatPass, a native iOS app for creating and managing Apple Wallet passes. TUM's iPraktikum deepened my iOS skills through a team project with industry partners. SwiftUI, SwiftData, and MapKit are now part of my daily toolkit.
C keeps me honest about what the machine is doing. I use it for reverse-engineering tools and performance-sensitive utilities, and TUM coursework keeps the memory model second nature.
I have been hands-on with large language models since the first GPT-3 release. These days I design prompting strategies, RAG and MoE pipelines, and agent-style workflows that move past demos and deliver dependable value for teams.
Machine learning hooked me as soon as I started coding. I've built custom models, shipped applied projects at work, and now steer my bachelor's and then master's degree toward ML to go deeper.
Shipping open source is nice, but real adoption needs a great interface. I grew from hand-written HTML and CSS to full TypeScript stacks, shipping sites like this portfolio and SaaS dashboards with resilient realtime backends and graceful fallbacks.
Docker used to feel intimidating, and now nearly everything I ship, from personal projects to university work and production services, runs in containers. It keeps environments predictable and turns deployments into a no-drama moment.
I'm comfortable modelling data across Postgres, DynamoDB, Redis, and friends. Picking the right store and keeping it healthy is core to how I build reliable systems.
As Westend61's system admin I take care of everything an office might need. That mix lets me debug anything from flaky Wi-Fi to firewall oddities without drama.
I leaned hard into cloud in 2024, mostly AWS. From containerised services to event-driven jobs, I automate the infrastructure so shipping features stays fast and safe.
I run weekly tutoring sessions, exam prep courses, and a peer community that helps classmates ramp up quickly. Speaking to rooms of 30 plus students keeps my teaching sharp.
Years of moving between software development, system administration, and teaching taught me to see technology as more than code. It’s an ecosystem. Managing servers, building APIs, and mentoring students all revealed how decisions ripple through a system. I’ve learned to think in connections, not components, designing solutions that stay coherent as they grow.
I genuinely enjoy crafting story-driven presentations. Weekly tutoring sessions and impromptu talks keep my pacing, visuals, and storytelling sharp. I'm also no stranger to presenting in front of large audiences.
Four years of LLM exploration since GPT-3, multiple weekend side projects, and a runner up finish at the TUM.ai Hackathon taught me to validate ideas through scrappy prototypes.
I treat ideas like lean experiments: talk to users, validate quickly, understand the operations, and iterate until a metric actually moves. SaaS work, my stealth startup and BWL courses sharpen that mindset.
