Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking an experienced Machine Learning Operations (MLOps) Engineer to join their cutting-edge AI & Emerging Technologies team in Nottingham . This role is crucial for bridging the gap between machine learning model development and reliable production deployment. You will be responsible for building and maintaining the infrastructure, tools, and processes that enable the efficient deployment, monitoring, and scaling of ML models. This is an exciting opportunity to work at the intersection of machine learning, DevOps, and cloud infrastructure, ensuring our client's AI initiatives are robust and scalable.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for training, deploying, and monitoring ML models at scale.
• Implement robust monitoring, logging, and alerting systems for ML applications in production.
• Automate ML workflows, including data validation, model training, and deployment processes.
• Collaborate closely with data scientists and software engineers to optimize ML model performance and reliability.
• Ensure security best practices are followed throughout the MLOps lifecycle.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in DevOps, software engineering, or MLOps, with a focus on machine learning systems.
• Strong proficiency in cloud platforms such as AWS, Azure, or GCP.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Knowledge of scripting languages (e.g., Python, Bash) and infrastructure-as-code tools (e.g., Terraform, Ansible).
• Understanding of machine learning concepts and workflows is essential for this role in Nottingham .

Benefits

• Competitive salary and annual performance reviews.
• Comprehensive health, dental, and vision insurance coverage.
• Generous training budget for cloud certifications and MLOps tools.
• Hybrid work model providing flexibility and work-life balance.
• Opportunity to work with advanced AI technologies and shape the future of MLOps at a leading company in Nottingham .