Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to establish and maintain robust production pipelines for their AI initiatives in Nottingham . You will be responsible for bridging the gap between machine learning development and deployment, ensuring that models are reliably built, tested, deployed, and monitored. This role is crucial for streamlining the ML lifecycle and enabling the efficient operationalization of advanced AI capabilities. We are looking for a proactive engineer who excels in automation, infrastructure management, and collaboration.

Key Responsibilities

• Design, build, and maintain scalable CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for ML model training, deployment, and monitoring.
• Automate model retraining, versioning, and deployment processes.
• Collaborate closely with data scientists and software engineers to ensure smooth integration.
• Monitor model performance in production and troubleshoot issues proactively.
• Implement best practices for MLOps, containerization, and cloud infrastructure.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience as an MLOps Engineer, DevOps Engineer, or similar role.
• Proficiency in scripting languages (e.g., Python, Bash) and CI/CD tools (e.g., Jenkins, GitLab CI).
• Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Docker, Kubernetes).
• Understanding of machine learning workflows and model deployment strategies.
• Strong problem-solving skills and a commitment to automation.

Benefits

• Competitive salary and performance-based incentives.
• Comprehensive health, dental, and vision insurance.
• Opportunities for professional development and training.
• Collaborative and forward-thinking work environment in Nottingham .
• Generous paid time off and pension scheme.
• Direct impact on operationalizing cutting-edge AI solutions.