Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their growing team in Liverpool . This crucial role bridges the gap between machine learning development and production deployment, ensuring that models are deployed efficiently, reliably, and scalably. You will be responsible for building and maintaining the infrastructure and workflows necessary to support the machine learning lifecycle, contributing directly to the operational success of advanced AI & Emerging Technologies projects. The position offers a flexible hybrid work arrangement, combining remote work with essential team collaboration.

Key Responsibilities

• Develop, implement, and maintain CI/CD pipelines for machine learning models.
• Automate the deployment, monitoring, and scaling of ML models in production environments.
• Build and manage infrastructure for ML experimentation, training, and inference.
• Implement monitoring solutions to track model performance, data drift, and system health.
• Collaborate closely with data scientists and software engineers to streamline the ML lifecycle.
• Ensure reproducibility, versioning, and governance of ML artifacts.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, Docker, Kubernetes).
• Proficiency in scripting languages such as Python.
• Understanding of cloud platforms (AWS, Azure, GCP) and infrastructure-as-code principles.
• Familiarity with machine learning concepts and workflows.
• Strong problem-solving skills and the ability to work in a team environment.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional development in the rapidly growing field of MLOps.
• Work on exciting AI and machine learning projects in Liverpool .
• Flexible hybrid working model.
• Access to modern technology and collaborative tools.