MedTech MLOps Architect: Regulated Model Lifecycle

NeuroTechX; Barcelona; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Private Health Insurance

Hybrid working modality

23 vacation days per year

Christmas week off

Udemy access

Training bonus

Job summary

Inbrain Neuroelectronics is seeking a Machine Learning Operations Architect to own model lifecycle governance and deployment infra. You will bridge MLOps with medical-device design-control, defining versioning, validation, and change-control protocols for adaptive models.

You will work across clinical, regulatory and software teams to ensure safe updates post-deployment, while enabling real-time healthcare solutions globally.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Electrical Engineering or a related field.
• 4–5 years hands-on ML Ops engineering experience in medtech or safety-critical environments.
• Experience shipping ML into regulated environments (IEC 62304, ISO 13485, DO-178C, ISO 26262).
• Experience with model versioning/registries and CI/CD for ML.
• Strong infrastructure-as-code skills and Python productionization.

Responsibilities

• Design and implement model versioning, lineage, and validation-evidence systems.
• Define PCCP-style framework for adaptive models and automated re-validation.
• Configure CI/CD pipelines for training, validation, and promotion of models across DTAP tiers.
• Build drift and performance monitoring with triggers for retraining and post-market surveillance.
• Maintain versioning and tracing aligned with design-control processes.

Skills

ML Ops experience

Model versioning/registries

CI/CD for ML

Containerized deployment

Workflow orchestration

Regulatory/safety-critical

English fluency

Technical documentation

Education

Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Electrical Engineering or related field

Tools

Kubernetes

MLFlow or equivalent

Argo or equivalent

Job description

Inbrain Neuroelectronics is seeking a Machine Learning Operations Architect to own model lifecycle governance and deployment infra. You will bridge MLOps with medical-device design-control, defining versioning, validation, and change-control protocols for adaptive models.

You will work across clinical, regulatory and software teams to ensure safe updates post-deployment, while enabling real-time healthcare solutions globally.