MLOps Engineer - Scale Production ML Pipelines

JobCloud SA | jobup.ch - jobs.ch; Porto; Hybrid; EUR 45,000 - 65,000; Full time

Benefits offered by this job

1 day per month to tackle challenges

Conference budget for trainings

Travel for workshops (Zurich, Geneva,,

Hybrid & flexible working

Job summary

JobCloud HR Tech in Porto, Portugal is seeking an experienced Machine Learning Ops Engineer to design end-to-end ML pipelines, deploy models into production, and ensure reliability at scale for the European market.

You'll collaborate with data scientists and cloud engineers, manage model serving infrastructure, and implement security and governance for ML systems. The role offers hybrid work, hands-on automation, and opportunities to travel for workshops.

Qualifications

• 2–3 years of experience in MLOps, DevOps, or related production ML roles.
• Experience deploying ML/AI prototypes into production.
• Strong cloud experience and container orchestration.
• Experience with CI/CD pipelines and Infrastructure as Code (IaC).

Responsibilities

• Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring.
• Collaborate with data scientists and cloud engineers to productionize ML models and establish best practices.
• Develop and maintain model serving infrastructure with focus on scalability, reliability, and low latency.
• Manage ML experiment tracking, model versioning, and model registry systems.
• Monitor model performance in production and implement alerting systems.
• Implement security best practices for ML systems and ensure compliance with data governance policies.
• Document MLOps processes, architecture decisions, and runbooks.

Skills

MLOps

Cloud platforms (AWS/GCP/Azure)

Kubernetes

CI/CD & IaC

Linux troubleshooting

ML frameworks (PyTorch/TensorFlow)

English

Tools

Docker

ECS

Job description

JobCloud HR Tech in Porto, Portugal is seeking an experienced Machine Learning Ops Engineer to design end-to-end ML pipelines, deploy models into production, and ensure reliability at scale for the European market.

You'll collaborate with data scientists and cloud engineers, manage model serving infrastructure, and implement security and governance for ML systems. The role offers hybrid work, hands-on automation, and opportunities to travel for workshops.