Your missionWe are scientists, doctors, techies and humanity lovers, with the mission of pioneering real time precision neurology to cure brain-related disorders.
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INBRAIN harnesses the extraordinary material properties of Graphene, the world’s thinnest and nobel-prize winning material, to build high resolution neural systems. Our mission is to decode and modulate neural networks to restore people's lives.As a Machine Learning Operations Architect, you will architect and own the model lifecycle governance and deployment infrastructure.
The role bridges MLOps engineering with medical-device design-control practice: it defines how models are versioned, validated, and promoted, and builds the change-control framework (aligned with a PCCP-style approach) that governs how adaptive, continuously-learning models can be safely updated post-deployment.



You will be at the forefront of bringing advanced healthcare solutions to market, making a tangible difference in peoples lives worldwide.Your profileMain Responsibilities:Design and build the model versioning, lineage, and validation-evidence system that ties every trained model to its training data, the data source origin, risk management, and clinical evidence.Draft and maintain a Predetermined Change Control Plan (PCCP)-style framework defining permitted modification types, bounds, and automated re-validation protocols for adaptive models, in collaboration with clinical, regulatory, product and software stakeholders.Design and configure the CI/CD pipeline for training, validating, and promoting models, running on infrastructure provided by the Software team, with promotion gates across Development, Testing, Acceptance and Production (DTAP) tiers.Build drift and performance monitoring for models and define triggers for scheduled vs.
drift-triggered retraining as

📌 Machine Learning Operations Architect (España)
🏢 Inbrain Neuroelectronics
📍 España