Senior MLOps & DevOps Engineer
Role details
Job location
Tech stack
Job description
As a Senior MLOps & DevOps Engineer, you will bridge clinical data and machine learning development workflows with product-grade software delivery and operational deployment.
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., * 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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Operational tasks
- 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)
Requirements
Do you have experience in Terraform?, * 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
Benefits & conditions
- 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