Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to enhance their AI capabilities in Stoke-on-Trent, Staffordshire, UK . This role focuses on bridging the gap between machine learning model development and reliable, scalable deployment. You will be responsible for building and maintaining the infrastructure, tools, and processes that enable the efficient development, deployment, monitoring, and management of machine learning models in production. This is a critical role for an engineer passionate about automation, CI/CD, and robust operational practices within the AI lifecycle.

Key Responsibilities

• Develop and maintain robust CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for training, deploying, and serving ML models at scale.
• Monitor the performance and health of production ML models, identifying and resolving issues proactively.
• Automate model retraining, versioning, and deployment processes.
• Collaborate closely with data scientists and software engineers to streamline the ML workflow.
• Implement best practices for data and model versioning, testing, and reproducibility.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in software engineering, DevOps, or MLOps roles.
• Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Familiarity with MLOps tools and best practices (e.g., MLflow, Kubeflow, Airflow).
• Strong understanding of CI/CD principles and practices.

Benefits

• Competitive salary and performance bonuses.
• Hybrid working model providing flexibility.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and holiday allowance.
• Opportunities for training and career advancement in the rapidly growing field of MLOps.