Machine Learning​/MLOps Engineer_Nottingham; ML Engineer II

Machine Learning / MLOps Engineer

Location: Nottingham, UK (Hybrid)

Employment Type: 6-Month Fixed-Term Contract / Contract Inside IR35

Start Date: Immediate

We are seeking a Machine Learning / MLOps Engineer to help build, deploy, and support production-ready machine learning solutions on Azure and Databricks. Working closely with Data Scientists, Data Engineers, Platform Engineers, and business stakeholders, you will be responsible for ope rationalising ML models, building scalable data and ML pipelines, implementing monitoring, and supporting the end-to-end ML lifecycle. This role will initially span MLOps, data engineering, and platform activities while the capability continues to mature.

• Deploy and ope rationalise machine learning models developed by Data Science teams.
• Build and maintain ML and data pipelines using Python, PySpark, SQL, Azure, and Databricks.
• Develop and manage Databricks Workflows, Jobs, MLflow, and model deployment processes.
• Implement CI/CD pipelines and Git-based development practices.
• Build monitoring and ing for model performance, data quality, workflow failures, and operational health.
• Manage model lifecycle activities including versioning, deployment, testing, and continuous improvement.
• Collaborate with platform, cloud, Dev Ops, security, and operational teams to ensure scalable and secure deployments.
• Create deployment documentation, runbooks, and support processes.

• Hands‑on experience as an ML Engineer, MLOps Engineer, or similar role.
• Strong experience with:
  • Azure Cloud
  • Databricks
  • Python, PySpark, SQL
  • MLflow and Databricks Workflows
  • CI/CD and Git
• Machine Learning deployment and operational support.
• Experience building and maintaining production‑grade ML pipelines.
• Understanding of model monitoring, observability, testing, and governance.
• Experience working across Data Science, Engineering, and Platform teams.
• Strong troubleshooting, communication, and stakeholder management skills.

• Generative AI / LLM development experience (Lang Chain, Lang Graph, RAG frameworks).
• Unity Catalog and Databricks Model Registry.
• Azure Dev Ops, Git Hub Actions.
• Docker, Kubernetes (AKS), Azure Container Apps.
• Terraform or Infrastructure‑as‑Code tools.
• Retail, forecasting, recommendation, or personalisation use cases.
• Azure or Databricks certifications.