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Dirk K.DK

Dirk K.

AI Engineer and Machine Learning Expert

€500/day
Zurich, CH
3-7 years

Average response time: 1 hour

About Dirk

I’m an AI engineer and researcher who spends an unreasonable amount of time teaching machines to see, read, and occasionally make sense of the world. I have 3+ years of hands-on experience developing explainable, data-efficient, and production-ready AI systems.

I’ve worked in leading research environments at Cambridge, Utrecht, and Konstanz, combining a research-driven mind set with real-world engineering in Python, PyTorch, TensorFlow, Ray, and Slurm. I’ve worked in leading research environments at Cambridge, Utrecht, and Konstanz, where I specialize in medical and biomedical data, building data-efficient deep learning pipelines for time-series analysis, and have also delivered projects in drone image analysis.

What sets me apart:
• Proven success bridging research and engineering — from concept to deployment
• Expertise in explainable AI and data-efficient learning for real-world reliability
• Fluent collaboration across scientific, engineering, and business teams
• Trilingual (English, German, Dutch) — ideal for EU-based, cross-national projects

Recent Highlights:
🔹 Developed an explainable multimodal medical foundation model at Cambridge
🔹 Co-authored a grant proposal on real-time neuroprosthetic AI frameworks (Utrecht)
🔹 Designed distributed training pipelines for large-scale healthcare data (Ray/Slurm)

I’m passionate about turning advanced AI research into scalable, interpretable systems that create measurable impact — from smarter vision systems to transparent decision models in healthcare, and I am looking to expand to domains outside of healthcare.
  • German

    Native or bilingual

  • English

    Fluent

  • Dutch

    Fluent

  • French

    Basic

Can work on-site
Zurich (up to 50km)

Experience

  • NeuroInformatics Lab [NIL]
    Visiting Scholar
    BIOTECH
    October 2024 - October 2025 (1 year)
    Cambridge, United Kingdom
    • Precision Neuroscience: Engineered cutting-edge multimodal GNNs improving loss by 35% vs. lab baseline.
    • Deployment: Scaled workflows using Ray / Slurm / GraphGym on HPC; built reproducible ML pipelines.
    • Team: Supervised graduate projects; advised ML integrations for precision neuroscience.
    Graph Neural Networks Deep Learning Precision Medicine Neuroimaging Data mining
  • Brain-Computer Interface Lab [BCI]
    Research Internship
    BIOTECH
    July 2023 - July 2024 (1 year)
    Utrecht, Netherlands
    • AutoML Decoding: Built AutoML for ECoG hand-movement decod ing: F1=96.6 (4-class).
    • Electrode-grid Optimization: Optimal size and location: –92% area with no F1 degradation.
    • Analytics Library: Feature-selection/analytics library using meta heuristics (modular, reusable).
    AutoML time series moddeling electrophysiology Brain-Computer Interface Machine learning
  • Müller's and Kalbitzer's Lab [ML-KL]
    Research Assistant
    TECH
    May 2023 - May 2024 (1 year)
    Konstanz, Germany
    • Data engineering: Built drone-imagery forest canopy datasets.
    • Canopy segmentation: Trained uncertainty-aware (abstaining) CNNs-ViT hybrid (InternImage) for canopy segmentation/recognition.
    Segmentation Object Recognition Data Engineer Computer Vision

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Education

  • M.Sc.
    University Utrecht
    2025
    M.Sc.
  • M.Sc.
    University Utrecht
    2024
    M.Sc.

Skill set

Categories