Healthcare MLOps Engineer: Scalable Production AI

Bloodflow; Viseu; Híbrido; EUR 60 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive compensation and benefits

Equity participation

Professional development and training

Impact on patient care

Resumo da oferta

BloodFlow is building an AI platform that interprets blood test results in a clinical context to aid doctors in decision-making. We’re deploying ML models with robust ML infrastructure, Kubernetes, and CI/CD pipelines to production.

You’ll work on scalable cloud and on-prem deployments, with a focus on reliability, security, and regulatory compliance. The role involves designing and maintaining production ML systems, monitoring performance and drift, and ensuring GDPR/HIPAA compliance in medical

Qualificações

• 3+ years experience in DevOps, MLOps, or production ML systems.
• Familiarity with Docker and cloud platforms.
• Experience with monitoring tools and infrastructure as code.
• Understanding of GDPR, HIPAA, or medical device compliance.

Responsabilidades

• Build and maintain ML infrastructure using Kubernetes, Docker, and cloud services.
• Implement CI/CD pipelines for AI model deployment and updates.
• Design scalable architectures for cloud and on-prem deployments.
• Manage model versioning, rollbacks, and A/B testing infrastructure.
• Implement monitoring for model performance and drift detection.
• Build dashboards and alerting for production AI systems.
• Track latency, accuracy, throughput, and resource utilization.
• Ensure healthcare audit/tracing compliance and data privacy.
• Implement security best practices for AI deployment.
• Support regulatory requirements for medical device certification.

Conhecimentos

DevOps/MLOps experience

Python

Docker

Cloud platforms

SRE knowledge

GDPR/HIPAA awareness

Ferramentas

MLflow

Kubeflow

Vector databases

Descrição da oferta de emprego

BloodFlow is building an AI platform that interprets blood test results in a clinical context to aid doctors in decision-making. We’re deploying ML models with robust ML infrastructure, Kubernetes, and CI/CD pipelines to production.

You’ll work on scalable cloud and on-prem deployments, with a focus on reliability, security, and regulatory compliance. The role involves designing and maintaining production ML systems, monitoring performance and drift, and ensuring GDPR/HIPAA compliance in medical