Machine Learning / MLOps Engineer_Nottingham (ML Engineer II)

UST
Nottingham, UK
about 1 month ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Microsoft Azure Cloud Computing Continuous Integration Information Engineering DevOps Github Monitoring of Systems Python (Programming Language) Machine Learning Runbook SQL Databases Management of Software Versions
+12 more
Large Language Models Software Troubleshooting Generative AI Git Pyspark Kubernetes Infrastructure Automation Frameworks Machine Learning Operations Terraform Data Pipelines Docker Databricks

Job description

Working closely with Data Scientists, Data Engineers, Platform Engineers, and business stakeholders, you will be responsible for operationalising 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 operationalise 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, DevOps, security, and operational teams to ensure scalable and secure deployments.
  • Create deployment documentation, runbooks, and support processes.

Requirements

  • 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.

Desirable Skills

  • Generative AI / LLM development experience (LangChain, LangGraph, RAG frameworks).
  • Unity Catalog and Databricks Model Registry.
  • Azure DevOps, GitHub Actions.
  • Docker, Kubernetes (AKS), Azure Container Apps.
  • Terraform or Infrastructure-as-Code tools.
  • Retail, forecasting, recommendation, or personalisation use cases.
  • Azure or Databricks certifications., machine learning,python,databricks,pyspark

About the company

UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients’ organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact-touching billions of lives in the process.

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