Senior MLOps & DevOps Engineer

Who are we?

Today, we build on this legacy with a forward-looking roadmap powered by AI innovation.

We value connection, curiosity, and collaboration. We take pride in delivering technology that truly makes a difference.

The role

As a Senior MLOps & DevOps Engineer, you will bridge clinical data and machine learning development workflows with product-grade software delivery and operational deployment.

This role requires a highly self-directed engineer who takes ownership, operates with a high degree of autonomy, drives system design and technical direction, and over time grows into leading a small team of engineers.

Working closely with Applied Research, validation, software development, testing, security, and operations teams, in this hands-on role you ensure secure, compliant, and reproducible AI-enabled releases within Medis products - spanning both ML lifecycle pipelines and DevOps delivery infrastructure.

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What you will do

• Drive system design and technical direction
• Define and implement best practices for integrating ML workflows into product delivery pipelines
• Establish standards for dataset and model versioning, reproducibility, and traceability
• Ensure ML and product delivery pipelines align with cybersecurity and medical device compliance expectations (IEC 62304, ISO 13485, GDPR, HIPAA, etc.)
• Contribute to platform roadmap and delivery planning with R&D leadership

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• Review, build, and maintain ML platform components for training, deployment, and inference
• Develop tooling that enables ML practitioners to experiment, version, deploy, and monitor models reliably
• Implement automated evaluation, validation, and promotion gates for AI models moving from research into product
• Design and maintain CI/CD pipelines for ML models and software
• Extend DevOps infrastructure with secure-by-design controls (IAM, secrets, scanning)
• Implement infrastructure-as-code for scalable and auditable environments
• Build observability for ML and product systems including telemetry pipelines, drift detection, alerting, and reliability monitoring
• Implement and support DTAP (Development, Test, Acceptance, Production) environments for both product software and ML-enabled components
• Ensure controlled promotion of releases and models across DTAP stages
• Integrate pipelines with Medis’ SaaS toolchain and cloud platforms (e.g., Atlassian stack, cloud ML services, monitoring platforms)
• Support hybrid infrastructure setups (on-premises and cloud)

• 5–10 years’ experience in DevOps, MLOps, or ML Platform Engineering
• Strong Python development and debugging skills
• Hands-on experience with ML lifecycle tooling (e.g., MLflow, Airflow, SageMaker, Azure ML)
• Experience with at least one major cloud platform (AWS preferred)
• Proficient in automation scripting (Bash, PowerShell) and experienced in designing CI/CD workflows with GitHub Actions, Jenkins, or similar platforms
• Expertise in containerization and orchestration (Kubernetes) for packaging, deploying, and scaling both ML workloads and production software services
• Experience with observability, monitoring, and logging using the Prometheus stack (Prometheus, Grafana, Alertmanager) and centralized logging solutions (ELK, Loki)
• Experience implementing CI/CD pipelines with automated testing and validation for ML-enabled systems
• Understanding networking, security, and compliant deployment in the regulated medical environment
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, etc.)
• Experience working in IEC 62304, ISO 13485 regulated environments

• A rewarding and competitive compensation package, with both fixed and variable components
• A pension plan with strong employer contribution
• Flexibility to purchase additional leave days
• A diverse, collaborative, and international team culture with colleagues across Europe, the US, and Asia
• The chance to work on innovative solutions that truly impact patient care and the future of cardiovascular healthcare
• A hybrid work model – 2 days per week in our Leiden office, with flexibility for the rest