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2 azure devops engineer jobs found in Nottingham, hybrid

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Nottingham azure devops engineer Hybrid
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Duration not stated  (1) 6 Months or more  (1)
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Contract Spy
Jul 14, 2026
Duration not stated
Machine Learning/MLOps Engineer at UST, Nottingham/Remote, 6 Months, £Contract Rate
Contract Spy Hybrid (Nottingham, UK)
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...
Contract Spy
Jul 07, 2026
6 Months or more
Machine Learning/MLOps Engineer at UST, Nottingham/Remote, 6 Months, £Contract Rate
Contract Spy Hybrid (Nottingham, UK)
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....
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