MLOps Engineer H/F

About the role

You will conceive and implement MLOps pipelines on Azure for projects involving Machine Learning, Computer Vision, and/or Natural Language Processing. You will deploy and manage Machine Learning models on Azure using Azure Machine Learning, Azure DevOps, and Kubernetes ecosystems. Your responsibilities include establishing monitoring and alerting solutions for both models and the MLOps infrastructure itself. You will ensure the quality of deployed code and models by enforcing rigorous testing standards such as unit tests and integration tests. You will work in close collaboration with Data Science teams and business stakeholders to translate requirements into technical solutions. You will contribute to the continuous enhancement of MLOps practices across the Ippon group. This role positions you at the intersection of cloud engineering and data science, driving impactful technological transformations.

Key facts

What you'll do

Orchestrate the design and delivery of robust MLOps pipelines on Microsoft Azure to support advanced analytics initiatives.

Deploy containerized Machine Learning models leveraging Azure Machine Learning workspaces and associated compute targets.

Implement CI/CD pipelines within Azure DevOps to automate the testing and deployment lifecycle of model artifacts.

Establish comprehensive monitoring frameworks to track model performance, data drift, and infrastructure health in production.

Configure alerting mechanisms to enable rapid response to anomalies or service degradation in deployed systems.

Conduct rigorous code and model validation through the implementation of unit tests, integration tests, and validation suites.

Collaborate with cross-functional Data Science teams to ensure alignment between technical implementation and business objectives.

Translate complex business requirements into scalable technical specifications for MLOps solutions.

Contribute to the definition and evolution of architectural standards for cloud-based Machine Learning operations.

Participate actively in code reviews and knowledge-sharing sessions to elevate the technical excellence of the team.

Engage with emerging best practices in MLOps to identify opportunities for process optimization and tooling improvements.

Support the full lifecycle of Machine Learning models from initial development through to decommissioning.

Champion automation initiatives to reduce manual intervention and increase reliability in operational workflows.

Act as a technical liaison between development teams and business units to ensure clarity of objectives.

Drive the adoption of containerization technologies to ensure consistency across development and production environments.

Requirements

Hold a degree in computer science, engineering, or a related technical field, or possess equivalent professional experience.

Bring a minimum of 1 year of professional experience as an MLOps consultant or in a similar cloud engineering role.

Demonstrate expert-level proficiency with Azure Machine Learning services and associated tooling.

Showcase a strong understanding of Azure DevOps principles and the ability to implement CI/CD workflows.

Exhibit solid knowledge of Kubernetes architecture, deployment strategies, and cluster management.

Possess hands-on experience with containerization technologies, specifically Docker, and container orchestration practices.

Display advanced programming skills in Python, including experience with major Machine Learning frameworks like scikit-learn, TensorFlow, and PyTorch.

Have a clear comprehension of core MLOps concepts including experiment tracking, model versioning, monitoring, and retraining strategies.

Provide evidence of at least one completed project utilizing Azure MLOps in a professional context.

Communicate effectively in both written and verbal formats, ensuring complex ideas are conveyed with precision.

Thrive in collaborative environments where cross-team cooperation is essential to achieving shared goals.

Exhibit a high level of autonomy, taking ownership of tasks and deadlines without constant supervision.

Show adaptability and resilience when working within complex and rapidly evolving technical landscapes.

Maintain a meticulous attention to detail to ensure the reliability and quality of delivered solutions.

Nice to have

Experience with cloud platforms such as AWS or GCP in addition to Azure.

Knowledge of Infrastructure as Code (IaC) tools like Terraform or Bicep.

Familiarity with monitoring tools such as Prometheus, Grafana, or Azure Monitor.

Understanding of data versioning tools like DVC or lakeFS.

Experience with low-code or no-code Machine Learning platforms.

Practical notes

This is a permanent contract (CDI).

Remote work is possible from any location.

Standard working hours apply.

Proficiency in French and English is required for client interactions and team collaboration.

Candidates must be authorized to work in France without sponsorship.

Ippon is an equal opportunity employer and welcomes applications from all qualified individuals.