MLOps (Machine Learning Ops) Engineer

Job Title: MLOps Engineer
Department: Data, Analytics & AI
Reports To: Head of Data Engineering / AI Solutions Architect

Role Overview

We are seeking an MLOps Engineer to build and maintain the infrastructure required to deploy, monitor, and scale machine learning models in production. This role is critical for ensuring reliability, automation, and governance across our AI and analytics ecosystem.

Key Responsibilities

• Build and maintain ML deployment pipelines
• Automate model training, testing, versioning, and release processes
• Monitor model performance, drift, uptime, and cost
• Manage CI/CD workflows for ML systems
• Collaborate with data scientists and engineers to productionize models
• Implement logging, observability, and rollback mechanisms
• Maintain cloud-based ML infrastructure and environments
• Ensure model governance, reproducibility, and documentation

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
• Strong experience with Python, Docker, Kubernetes, and CI/CD pipelines
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Airflow, or similar
• Knowledge of AWS, Azure, or GCP
• Understanding of model serving, monitoring, and infrastructure automation

Preferred Qualifications

• Experience with LLMOps and serving generative AI models
• Familiarity with Terraform, Helm, feature stores, and model registries
• Experience in production ML environments at scale