MLOps Engineer: Data Infra & Pipelines Architect

Jobless; Nice; Hybride; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Jobless is seeking an experienced MLOps Engineer to build and operate the data infrastructure for our ML platform in France. This hands-on role sits at the intersection of data engineering, DevOps and infrastructure, focusing on data pipelines, versioning, and offline/isolated environments.

You will own bare-metal and VM provisioning, automation, and monitoring, collaborating with ML, Data and Software Engineers to ensure seamless training and inference workflows.

Qualifications

• Strong hands-on Linux experience with command line proficiency.
• Experience configuring and managing servers, VMs and infrastructure.
• Hands-on knowledge of Docker and containerised environments.
• Experience building offline or restricted-network environments.
• Practical use of ML tooling like MLflow, DVC, ClearML or similar.
• Proficiency in Python scripting for automation and integration.
• Understanding of data pipelines and ML deployment workflows.
• Experience implementing CI/CD for software, data or ML workloads.
• Good understanding of Git workflows and version control.
• Fluent English, written and spoken.

Responsabilités

• Design, configure and maintain servers, VMs and environments for data pipelines and ML development.
• Build and maintain infrastructure and automation for data collection, prep, validation, versioning and availability.
• Automate data flow from collection through preparation to downstream triggers.
• Configure Linux-based environments and servers used by ML and data teams.
• Deploy and maintain ML/data management platforms such as MLflow, DVC, ClearML.
• Create reproducible offline environments including local mirrors and private registries.
• Implement dataset/versioning and experiment traceability features.
• Operate and monitor the orchestration layer as a service; coordinate with the Data Engineer.
• Support management of large, varied datasets (images, video, time-series).
• Integrate data pipelines with training and inference setup; containerise data apps with Docker.
• Develop automation for provisioning, testing, deployment and monitoring.
• Define infrastructure monitoring and data-quality checks with input from Data Engineer.
• Monitor ML workloads, troubleshoot performance and availability issues.
• Optimize compute and storage usage for data processing.

Connaissances

Linux

Python

CI/CD

Git

Docker

MLflow

DVC

ClearML

Automation

Troubleshooting

English

Outils

Docker

MLflow

DVC

ClearML

Container registries

Description du poste

Jobless is seeking an experienced MLOps Engineer to build and operate the data infrastructure for our ML platform in France. This hands-on role sits at the intersection of data engineering, DevOps and infrastructure, focusing on data pipelines, versioning, and offline/isolated environments.

You will own bare-metal and VM provisioning, automation, and monitoring, collaborating with ML, Data and Software Engineers to ensure seamless training and inference workflows.