I design and build applied AI systems that turn advanced research into robust, usable solutions for real-world environments.
I am a Senior Applied Machine Learning Engineer focused on transforming complex AI research into practical, reliable systems that people can actually use. My work covers the full lifecycle of applied machine learning, from problem definition and system architecture to deployment and long-term operation.
I specialize in building AI platforms for users without a machine learning or HPC background, working closely with domain experts, IT teams, and stakeholders to ensure that technical solutions fit real organizational and infrastructural constraints. For me, AI does not exist in isolation: models, data, infrastructure, governance, and usability must work together to create lasting value.
Over the years, I have worked at the intersection of research, engineering, and operations, developing systems such as large-scale image analysis platforms and sovereign LLM infrastructures in regulated environments. I care deeply about responsible, human-centered AI and believe that sustainable AI adoption requires transparency, trust, and collaboration across disciplines.
- • End-to-end applied machine learning systems
- • AI platforms built for real users, not just demos
- • Bridging research, infrastructure, and application
- • Strong focus on usability, governance, and long-term operation
Feel free to explore my projects, technical demos, and (soon) blog posts — or reach out if you would like to discuss applied AI, platforms, or collaboration.
Hi, I'm Alexander Zeilmann.
I am an AI Solutions Engineer and Computer Scientist driven by a single motto: Making AI and Technology Accessible.
My work bridges the gap between complex algorithms and real-world needs, turning advanced research into clear, practical solutions. I believe the industry is facing a critical "Usability Gap," where powerful tools exist but remain out of reach for the domain experts who need them most. My mission is to close this divide.
With over 10 years of experience in machine learning and 20 years in software development, I architect and deliver scalable AI and web systems end-to-end. Whether leading the interdisciplinary KI-Morph initiative to democratize large-scale image analysis or developing YoKI, a sovereign LLM platform for Heidelberg University, I focus on moving ideas from concept to production.
I combine deep technical expertise with a service-oriented mindset, aligning users, scientists, engineers, and business stakeholders to ship products that create measurable value.
Explore my work to see how I translate technical innovation into accessible, high-impact solutions.
I am an AI Solutions Architect and PhD Researcher based in Heidelberg. For the past decade, my mission has been simple: bridge the gap between complex algorithms and the people who rely on them.
With over 20 years of programming experience and ten years in machine learning, I don't just research technology—I build it. From architecting KI-Morph, a platform that enables biologists to analyze massive 3D datasets with ease, to developing YoKI, Heidelberg University's sovereign LLM platform, I specialize in turning cutting-edge research into robust, user-friendly production systems.
My background blends academic rigor with industry pragmatism. Having consulted for both DAX corporations and startups, I know that even the best code is useless if it doesn't solve a real human problem. I thrive at the intersection of technical architecture, strategic management, and multidisciplinary collaboration—translating "business goals" into "technical reality" and back again.
Whether I'm fine-tuning a model, presenting a roadmap to stakeholders, or teaching the next generation of data scientists, my focus stays the same: Empowering others to do their best work using the best tools available.
Let's connect and build something meaningful.