Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their advanced AI team in Norwich . This role is crucial for bridging the gap between machine learning model development and seamless production deployment. You will be responsible for building and maintaining the infrastructure, tools, and processes required to deploy, monitor, and manage ML models at scale. This is an exciting opportunity to work with cutting-edge technologies, ensuring the reliability and efficiency of our AI systems, and collaborating with data scientists and software engineers to accelerate the delivery of ML-driven solutions.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for training, deploying, and monitoring ML models.
• Automate ML workflows, including data preparation, model training, and model validation.
• Implement monitoring solutions to track model performance, drift, and system health.
• Collaborate with data scientists and engineers to ensure robust and scalable ML deployments.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in DevOps, SRE, or MLOps, with a focus on ML systems.
• Proficiency in cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with scripting languages (Python) and infrastructure-as-code tools.
• Solid understanding of the machine learning lifecycle and common ML frameworks.

Benefits

• Competitive salary and comprehensive benefits package.
• Opportunities to work on challenging MLOps problems and learn new technologies.
• Be part of a team driving the operational excellence of AI solutions.
• A collaborative and innovative work environment in Norwich .
• Support for continuous professional development and training.