Ramtin Zargari Marandi
Science, engineering, and ideas into practice.
I am a scientist and engineer with over 10 years of experience in Denmark across academic research, AI/ML, and software engineering.
My work spans healthcare, life sciences, insurance, and technology, collaborating with international teams and stakeholders. I combine a foundation in engineering and scientific research with hands-on experience in AI/ML, software and platform architecture, and the systems that support them.
Working across academia and industry has given me a broad perspective on the full lifecycle of data, software, and IT systems—from early research and design to deployment and long-term operation.
Current expertise
I am currently a Senior AI/ML Architect at Aeven, which I joined in May. My recent work in cloud infrastructure and platform engineering complements my experience in AI/ML, helping me design, integrate, and operate models within larger systems.
Sovereign infrastructure & AI
Understanding control over data, infrastructure, and model dependencies—and how these choices shape AI architecture.
AI-assisted development
Applying coding assistants with attention to review, validation, maintainability, and software quality.
AI agents
Working with the concepts behind tool use, workflow orchestration, and evaluation of agent behavior.
Foundation models & evaluation
Following models for time-series forecasting, anomaly detection, and tabular prediction, with an emphasis on application-specific evaluation.
Observability & DevOps
Hands-on experience with observability and DevOps practices, using open-source tooling to support monitoring, delivery, and reliable operation of systems.
Kubernetes & open-source infrastructure
Hands-on experience with Kubernetes and its surrounding open-source ecosystem, connecting infrastructure operations with the needs of AI and ML systems.
Selected work
Open-source · Clinical ML
Medical AI Toolbox (MAIT)
An open-source Python framework for developing and validating machine learning models in clinical research.
More about my work →Explainability · R
ExplaineR
An R package integrating SHAP-based interpretability for transparent and reproducible medical AI.
Explore selected projects →Industry · Production ML
Automated claims AI
Development of production ML pipelines for insurance claims processing across multiple European markets.
Research · Human performance
Fatigue & oculometrics
Research on objective fatigue assessment using eye movement dynamics.
View publications →Research foundations. Industry experience.
My background is in biomedical engineering, with a PhD from Aalborg University. During my postdoctoral work at the Center of Excellence for Health, Immunity and Infections (CHIP) at Rigshospitalet, I worked on personalized medicine, infectious diseases, and the human gut microbiome, including predictive models for clinical outcomes and SHAP-based explanations.
In industry, I have developed and maintained AI systems in regulated environments, focusing on scalable pipelines, monitoring, and reproducibility. This experience shapes how I assess new AI capabilities: through their reliability, transparency, and usefulness in practice.
Advisory roles & new ventures
Alongside my technical work, I have contributed to open-source projects, published and reviewed scientific research, and advised and supervised researchers and technical specialists, including data scientists.
I am open to board, scientific committee, and technical advisory roles where my experience could be useful and where I can also learn from others. I value work that addresses a real need and has the potential to make a lasting contribution.
I would also welcome conversations about co-founding a venture with complementary partners. For me, that starts with a worthwhile problem, a sound idea, and people willing to test it carefully and build something useful together.
For conversations about AI/ML architecture, sovereign AI, AI-assisted development, agents, model evaluation, or applied research, reach me via email, LinkedIn, or GitHub.