Machine Learning Operations (MLOps) Engineer

About the Role

Our client is looking for an experienced Machine Learning Operations (MLOps) Engineer to build and maintain the infrastructure and processes that support our machine learning lifecycle. This hybrid role, offering flexibility between our Derby office and remote work, is critical for ensuring the reliable and scalable deployment of our AI models. You will bridge the gap between data science and operations, implementing best practices for automation, monitoring, and continuous integration/continuous deployment (CI/CD) of ML systems. This is a vital position for an individual passionate about operationalizing AI and ensuring its smooth integration into production environments.

Key Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model training, deployment, and monitoring.
• Implement CI/CD practices for machine learning models and infrastructure.
• Develop and manage infrastructure for model serving, scaling, and performance optimization.
• Monitor ML systems in production, identifying and resolving issues proactively.
• Collaborate with data scientists and software engineers to streamline the ML workflow.
• Automate data validation, model retraining, and deployment processes.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proficiency in scripting languages (e.g., Python, Bash) and containerization technologies (Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Understanding of machine learning concepts and workflows.
• Familiarity with CI/CD tools and practices.

Benefits

• Competitive salary and performance-related bonus.
• Comprehensive health and wellness benefits package.
• Pension scheme with employer match.
• Hybrid working model providing work-life balance.
• Opportunities for continuous learning and professional development in a growing field.