Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a proactive Machine Learning Operations (MLOps) Engineer to join their advanced AI team in Nottingham . This role is critical for bridging the gap between machine learning model development and production deployment, ensuring seamless integration, scalability, and reliability. You will be responsible for implementing and managing the infrastructure, tools, and processes required for the end-to-end machine learning lifecycle. Join a company dedicated to leveraging state-of-the-art AI and Emerging Technologies to drive innovation and efficiency.

Key Responsibilities

• Develop, implement, and maintain CI/CD pipelines for machine learning models.
• Automate the deployment, monitoring, and management of ML models in production environments.
• Build and optimize data pipelines and infrastructure for training and serving ML models.
• Collaborate with data scientists and software engineers to ensure smooth model lifecycle management.
• Implement monitoring solutions to track model performance, drift, and system health.
• Ensure the scalability, reliability, and security of ML platforms and services.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proven experience with CI/CD tools and practices for machine learning.
• Strong understanding of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Proficiency in programming languages like Python and scripting.
• Experience with ML frameworks and tools such as MLflow, Kubeflow, or TensorFlow Extended.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision coverage.
• Generous paid time off and company pension plan.
• Opportunities for professional development and learning in the AI domain.
• A collaborative and innovative work environment in Nottingham .