Machine Learning Engineer

Queen Square Recruitment; Wokingham; On-site; GBP 77,000 - 96,000; Full time

Job summary

Queen Square Recruitment is seeking an experienced Azure MLOps Engineer to deploy, automate, and manage ML solutions in Azure. You will work with architects, data scientists, and DevOps to deliver scalable, secure ML platforms for large-scale data processing and real-time inference workloads.

The role requires 5+ years in MLOps/DevOps, strong Python and ML framework experience, and hands-on Azure Machine Learning expertise.

Qualifications

• 5+ years' experience in MLOps, DevOps, or related engineering roles.
• Strong knowledge of the ML lifecycle and production ML operations.
• Hands-on experience with Azure Machine Learning and MLOps frameworks.
• Experience with Azure DevOps, CI/CD pipelines, and automation.
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with Docker, Azure SQL Database, Storage Accounts, Blob Storage, and SQL/NoSQL technologies.
• Experience monitoring production ML environments.
• Knowledge of data engineering practices and tools.
• Desirable: Azure Data Scientist Associate certification.

Responsibilities

• Deploy and manage ML models in production using Azure Machine Learning.
• Design and maintain Azure-based MLOps infrastructure.
• Build and support Azure DevOps CI/CD pipelines for ML artefacts.
• Implement monitoring, logging, security, and governance controls.
• Manage data pipelines, storage solutions, data versioning, and lineage tracking.
• Support real-time inference and scalable ML workloads, including auto-scaling.
• Collaborate with technical and business stakeholders to optimise model performance and platform reliability.
• Produce and maintain technical documentation.

Skills

MLOps

DevOps

Azure Machine Learning

Python

Docker

Azure SQL Database

Storage Accounts

Blob Storage

Real-time inference

Tools

Azure DevOps

TensorFlow

PyTorch

Scikit-learn

Docker

Job description

Location: Wokingham - Office based (hybrid working with 3+ days per week onsite may be considered)

Start Day: ASAP

Contract Rate: £460 per day inside IR35

Duration: 6 months initially

Role Overview

Our client is seeking an experienced Azure MLOps Engineer to support the deployment, automation, and management of machine learning solutions within Azure. Working closely with architects, data scientists, forecasting teams, developers, and DevOps engineers, you will help deliver scalable, secure, and reliable MLOps platforms supporting large-scale data processing and real-time inference workloads.

Key Responsibilities

• Deploy and manage ML models in production using Azure Machine Learning.
• Design and maintain Azure-based MLOps infrastructure.
• Build and support Azure DevOps CI/CD pipelines for ML artefacts.
• Implement monitoring, logging, security, and governance controls.
• Manage data pipelines, storage solutions, data versioning, and lineage tracking.
• Support real-time inference and scalable ML workloads, including auto-scaling.
• Collaborate with technical and business stakeholders to optimise model performance and platform reliability.
• Produce and maintain technical documentation.

Skills & Experience

• 5+ years' experience in MLOps, DevOps, or related engineering roles.
• Strong knowledge of the ML lifecycle and production ML operations.
• Hands-on experience with Azure Machine Learning and MLOps frameworks.
• Experience with Azure DevOps, CI/CD pipelines, and automation.
• Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
• Experience with Docker, Azure SQL Database, Storage Accounts, Blob Storage, and SQL/NoSQL technologies.
• Experience monitoring and supporting production ML environments.
• Knowledge of data engineering practices and tools.
• Familiarity with GRIB, NetCDF, Parquet, and JSON is advantageous.
• Azure Data Scientist Associate certification is desirable.