Senior MLOps Engineer

Summary

Join Xebia, a global leader in digital solutions, and become a key member of our team. Collaborate with Platform Engineers to build and maintain the infrastructure for efficient MLOps processes. Implement ML workflows, automate CI/CD pipelines, and deploy and monitor machine learning models. Work with stakeholders to identify and address challenges in machine learning project lifecycles. Stay current on the latest advancements in data engineering and machine learning. This role requires strong collaboration skills and a deep understanding of MLOps principles and technologies. Xebia offers a dynamic work environment and opportunities for professional growth.

Requirements

• 2+ years of experience developing and deploying machine learning systems into production
• 5+ years of experience as a MLOps engineer or data engineer or software developer
• Hands-on experience with cloud environments (AWS / Azure / GCP)
• Experience with tools such as Spark, PyTorch, TensorFlow and MLFlow
• Knowledge of DevOps practices and tools, including Terraform
• Experience with Docker and Kubernetes
• Understanding of continuous integration and continuous deployment (CI/CD) practices, as well as experience with related tools like GitHub Actions or GitLab CI
• Excellent verbal and written communication skills in English
• Work from the European Union region and a work permit are required
• Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation_customs/vies

Responsibilities

• Collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently
• Implementing ML workflows / automating CI/CD pipelines
• Automating model deployment and implementing model monitoring
• Collaborating with Platform Engineers to implement backup and disaster recovery processes for ML workflows, especially models and experiments
• Collaborating with stakeholders to understand the key challenges and inefficiencies of Machine Learning project lifecycles within the company
• Keeping on top of the latest trends and advancements in data engineering and machine learning

Preferred Qualifications

• Cloud (Azure, AWS, GCP) certification is a big plus
• Familiarity with Amazon SageMaker / Azure Machine Learning / VertexAI is nice to have