About the job
On behalf of our client, one of the Big Four firms in Netherlands, we are looking for a

DevOps / MLOps Engineer with a strong focus on Google Cloud Platform (GCP) to join our team and work remotely.

Role Summary
You will lead the design, deploy, and maintain scalable infrastructure and machine learning pipelines. You will collaborate with software engineers, data scientists, and ML engineers to build automated, reliable, and secure ML operations that accelerate model delivery from development to production.

Key Accountabilities

• Design, implement, and maintain CI/CD pipelines for both software and machine learning workflows using Cloud Build, GitHub Actions, or Jenkins.
• Develop and manage Infrastructure as Code (IaC) with Terraform and Google Deployment Manager.
• Build, deploy, and manage containerized applications and ML models using Docker and Google Kubernetes Engine (GKE).
• Automate ML model training, evaluation, deployment, and retraining pipelines using Vertex AI Pipelines, Kubeflow, or Apache Airflow.
• Manage data and model versioning with MLflow, DVC, or Vertex AI Model Registry.
• Implement monitoring, logging, and alerting solutions with Google Cloud Operations Suite (Stackdriver).
• Ensure high availability, scalability, and security across GCP resources (IAM, VPCs, Secrets Manager, Cloud Armor).
• Collaborate with data scientists to integrate models into production APIs or real-time prediction services using Vertex AI Endpoints or Cloud Run.
• Enforce MLOps best practices around reproducibility, governance, and model lifecycle management.
• Support cost optimization, performance tuning, and reliability engineering initiatives across ML workloads.

Knowledge, Skills & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or equivalent.
• 3+ years of experience as a DevOps, Cloud, or MLOps Engineer.
• Proven hands-on experience with Google Cloud Platform (GCP) services such as:
• Compute Engine, Cloud Run, GKE, Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Functions.
• Proficiency with CI/CD tools: Cloud Build, GitHub Actions, or Jenkins.
• Experience with Terraform or other IaC tools for automated infrastructure provisioning.
• Strong background in containerization and orchestration (Docker, Kubernetes, Helm).
• Good understanding of Python and experience supporting ML workflows (scikit-learn, TensorFlow, or PyTorch).
• Familiarity with monitoring and logging tools (Stackdriver / Cloud Operations Suite, Prometheus, Grafana).
• Solid knowledge of Git workflows and automated testing.

Benefits

• Attractive remuneration package aligned with seniority.
• Unique growth opportunity working with true innovators and in large-scale, international client projects.
• Continuous personal development and international training opportunities.
• Fully remote or flexible working environment.