Azure MLOps Engineer

What this role looks like

Automated interpretation based only on the supplied job description. This is not the original job description.

What the role is really about: The supplied brief points to a role primarily centred on operational support and reliability. Alongside that, it places meaningful emphasis on hands-on engineering and build work, automation and DevOps practices, and implementation and delivery.

What you would actually be doing: In practical terms, the work described covers building and developing technical solutions, shaping technical designs and solution decisions, supporting live services, resolving issues and maintaining reliability, and automating delivery and improving engineering/deployment workflows.

What this role expects from you as an applicant: The source explicitly asks for Design and manage Azure cloud resources required for model hosting and inference; Mandatory / essential skills; and demonstrable experience building and automating cloud-based ML platforms. The JD also looks for 5+ years' experience in MLOps, DevOps, Machine Learning Engineering, or a related field; strong understanding of machine learning concepts and model lifecycle management; and Deep understanding of software engineering principles and ML model deployment. The role's Core Skills also point to application-development capability around Python; delivery, testing and engineering practices including CI/CD; data capability across SQL; and additional core capability in Data Pipelines, TensorFlow, PyTorch, and scikit-learn.