Consultant MLOps Engineering

📋 Job Overview

Join Comma as an MLOps Engineer, where you'll play a key role in designing and implementing MLOps infrastructures and automation solutions for customer projects.

🏢 About Comma

Comma is a company focused on providing MLOps solutions to help organizations effectively deploy and manage machine learning models in production.

🎯 The Role

As an MLOps Engineer at Comma, you will be responsible for multiple roles depending on the customer project needs, including technical expert, implementer, and enabler.

✅ Key Responsibilities

• Act as the primary technical contact for the conception and implementation of MLOps infrastructures and automation solutions
• Build platforms and pipelines, configure tools, and write necessary code (IaC, CI/CD configurations, automation scripts)
• Help Data Science teams and other stakeholders effectively use MLOps platforms and processes to successfully bring ML models into production
• Coordinate technical requirements at the interface between Data Science, Software Development (DevOps), IT Operations, and potentially Security to integrate solutions
• Follow current developments in MLOps and DevOps and learn to evaluate and implement new technologies
• Work with experienced colleagues on the conception, development, and further development of MLOps platforms, including the design of technical infrastructure and toolchains (e.g., based on Kubeflow and Kubernetes) to support and automate the entire machine learning lifecycle
• Support the deployment of ML models and contribute to the automation of workflows through CI/CD pipelines (e.g., with GitLab CI/CD or GitHub Actions) – including troubleshooting and support
• Help with the integration and operation of central MLOps tools like MLflow for experiment tracking, model registry, and deployment and learn to integrate these into CI/CD processes
• Contribute to the implementation of GitOps practices (e.g., with Argo CD) for automated delivery of infrastructure and applications
• Support the setup of monitoring and logging solutions to monitor platforms, pipelines, and production ML models
• Work with Security teams to implement DevSecOps practices (e.g., container scanning, secret management, access controls) and learn how to integrate security into automated processes

🎁 Benefits

Competitive salary and benefits package.