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Machine Learning Engineer

AI Futures • Berlin, Germany
100% English First Est. €72,000 - €95,000 / year
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Job Specifications & Overview

  • Employer: AI Futures
  • Location: Berlin, Germany
  • Employment: Fulltime
  • *Medical Imaging AI Scale\-Up \| Germany \| €95k – €115k \+ Equity \| Permanent**

    • AI Futures has been engaged by the Co\-Founder \& CTO of one of Germany's best\-funded medical imaging AI companies to build out the machine learning team. This is a senior individual contributor hire with a clear route to lead.

  • *The company**

    • A venture\-backed medical imaging company and CE\-marked software live in radiology practices and hospitals across Europe. Their models read \[CT and MRI/whole\-slide pathology] in production, every day, on real patients.

    They are past the question of whether the technology works. The question now is whether it works everywhere: on every scanner, in every hospital, at a volume that doubles annually.

  • *The role**

    • As a ML Engineer you will own models end to end \- from the training pipeline to what happens when a radiologist disagrees with the output on a Tuesday morning.

    This is production ML in a regulated environment. You build the model, you build the evaluation that proves it, and you own the evidence when a notified body asks how you know. The hard part is not the architecture. It is generalisation: a model that performs on your validation set and falls over on a scanner it has never seen is not a product.

    You will be working alongside in\-house radiologists and pathologists who review the output and tell you, in detail, when it is wrong.

  • *What you'll do**
  • Build and ship segmentation and classification models on 3D volumes or gigapixel whole\-slide images * Own the evaluation framework \- define what "good enough" means for a clinical claim, and prove it holds across sites, scanners and patient populations * Work directly with in\-house clinicians on annotation strategy and edge\-case review * Build the monitoring that catches performance drift after deployment, not before * Produce the technical evidence that supports regulatory submission under EU MDR
  • *What you'll bring**
  • **Production ML, not research ML** \- you have shipped models people depend on, and you have been on the receiving end when one failed * **Python and PyTorch** \- essential. Experience with nnU\-Net, MONAI or equivalent medical imaging frameworks a strong advantage * **Medical imaging data in the real world** \- DICOM that does not conform to spec, inconsistent tagging, ground truth two experts disagree on * **Evaluation rigour** \- you are as interested in how the model fails as in how it performs * Comfort working with clinicians who will challenge your output directly
  • *Desirable**
  • EU MDR or FDA submission experience * Whole\-slide image handling at gigapixel scale, or 3D volumetric segmentation * Foundation models applied to medical imaging * MLOps: MLflow, Kubernetes, cloud training infrastructure
  • *Package \& Details**

    • €95,000 – €115,000 base \+ equity

    Permanent \| Hybrid.

    AI Futures have been engaged exclusively for this search.

    If this sounds like an exciting challenge to you please apply below.

  • *AI Futures \| Filling the AI Skills Gap ®**