UST

Machine Learning / MLOps Engineer_Nottingham (ML Engineer II)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning / MLOps Engineer in Nottingham, UK, on a 6-month fixed-term contract, with an immediate start. Key skills include Azure, Databricks, Python, and CI/CD. Experience in production-grade ML pipelines and collaboration across teams is essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 7, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Inside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
Nottingham, England, United Kingdom
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🧠 - Skills detailed
#MLflow #AI (Artificial Intelligence) #Security #Azure #Python #Data Pipeline #SQL (Structured Query Language) #Langchain #PySpark #Spark SQL #Deployment #Spark (Apache Spark) #Docker #Data Science #Monitoring #Cloud #Data Quality #Documentation #Scala #Azure DevOps #Model Deployment #Forecasting #Kubernetes #ML (Machine Learning) #Terraform #GIT #Data Engineering #Observability #DevOps #Azure cloud #Databricks #GitHub
Role description
Role Description 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 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. Key Responsibilities • 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. Essential Skills & Experience • 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. Hurry & apply for a more detailed conversation! #UST Skills machine learning,python,databricks,pyspark,