Azure Mlops Engineer - Inside IR35 - Onsite

Hamilton Barnes; Wokingham; On-site; GBP 71,000 - 96,000; Part time

Job summary

Hamilton Barnes is seeking an experienced Azure MLOps Engineer to join a contract-based team in Wokingham, UK. You will build, deploy, and maintain scalable ML solutions on Microsoft Azure, partnering with Data Scientists and DevOps to deliver reliable, secure platforms.

This 6-month, office-based role requires strong Python, Docker, and Azure ML skills, plus experience with CI/CD pipelines and production ML life cycle management.

Qualifications

• 5+ years of experience in MLOps/DevOps or related field.
• Strong proficiency with Azure Machine Learning.
• Hands-on experience with Azure DevOps CI/CD pipelines.
• Strong Python programming skills.
• Experience with Docker and containerized deployments.
• Good understanding of the ML life cycle and production deployment.
• Experience with Azure SQL Database, Azure Storage, and SQL/NoSQL databases.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience monitoring and supporting production ML models.

Responsibilities

• Deploy ML models into Azure production environments.
• Design, implement, and maintain Azure MLOps infrastructure.
• Build and manage CI/CD pipelines for ML solutions using Azure DevOps.
• Containerize applications and ML models using Docker.
• Monitor model performance, health, and reliability in production.
• Implement logging, monitoring, and alerting solutions.
• Optimize infrastructure for scalability, performance, and cost efficiency.
• Implement automated deployment and scaling strategies.
• Manage Azure cloud resources supporting ML workloads.
• Ensure security, governance, and compliance with data protection standards.
• Manage data pipelines, storage, versioning, and lineage.
• Collaborate with cross-functional teams to support end-to-end ML life cycle management.
• Troubleshoot production issues and continuously improve platform performance.
• Maintain technical documentation and communicate effectively with both technical and non-technical stakeholders.

Skills

MLOps experience

Azure Machine Learning

Azure DevOps CI/CD

Python

Docker

ML lifecycle knowledge

Azure SQL / Storage

TensorFlow / PyTorch

Production ML monitoring

Tools

Docker

Azure DevOps

Azure Machine Learning

Azure SQL Database

Azure Storage

TensorFlow

PyTorch

Scikit-learn

Job description

Job Title: Azure MLOps Engineer

Location: Wokingham, UK
Employment Type: Contract
Duration: 6 months
Work Mode: Office-based (5 days per week)
Rate: Up to £450/day

About the Role

We are looking for an experienced Azure MLOps Engineer to join a growing team responsible for building, deploying, and maintaining scalable machine learning solutions on Microsoft Azure. You will work closely with Data Scientists, DevOps Engineers, Architects, and Software Developers to deliver reliable, secure, and automated MLOps platforms supporting large-scale data processing and production ML workloads.

Key Responsibilities

• Deploy machine learning models into Azure production environments.
• Design, implement, and maintain Azure MLOps infrastructure.
• Build and manage CI/CD pipelines for machine learning solutions using Azure DevOps.
• Containerize applications and ML models using Docker.
• Monitor model performance, health, and reliability in production.
• Implement logging, monitoring, and alerting solutions.
• Optimize infrastructure for scalability, performance, and cost efficiency.
• Implement automated deployment and scaling strategies.
• Manage Azure cloud resources supporting ML workloads.
• Ensure security, governance, and compliance with data protection standards.
• Manage data pipelines, storage, versioning, and lineage.
• Collaborate with cross-functional teams to support end-to-end ML life cycle management.
• Troubleshoot production issues and continuously improve platform performance.
• Maintain technical documentation and communicate effectively with both technical and non-technical stakeholders.

Required Skills & Experience

• 5+ years' experience in MLOps, DevOps, or a related field.
• Strong experience with Azure Machine Learning.
• Hands-on experience with Azure DevOps CI/CD pipelines.
• Strong Python programming skills.
• Experience with Docker and containerized deployments.
• Good understanding of the machine learning life cycle and production deployment.
• Experience with Azure SQL Database, Azure Storage (Blob Storage), and SQL/NoSQL databases.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience monitoring and supporting production ML models.
• Knowledge of infrastructure automation and scalable cloud architectures.
• Experience supporting Real Time inference using Azure Machine Learning.

Desirable Skills

• Azure Data Scientist Associate certification.
• Experience with data engineering tools and practices.
• Familiarity with GRIB, NetCDF, Parquet, and JSON data formats.
• Experience working with enterprise MLOps frameworks.