Mlops Engineer (Azure ML Specialist) - £438 Inside IR35 - Hybrid

Stealth IT Consulting; Greater London; Hybrid; GBP 100,000 - 110,000; Full time

Job summary

Stealth IT Consulting seeks an MLOps Engineer (Azure ML Specialist) for a 6-month hybrid assignment in London. You will assess the existing Azure ML estate, document workflows, and support workload migration.

You will analyse training and deployment pipelines, model artefacts, and data flows; document dependencies and integrations; and provide migration and optimisation recommendations to enable production readiness.

Qualifications

• Strong hands-on Azure ML experience.
• Python and machine learning frameworks.
• Azure DevOps, CI/CD, and model life cycle management.
• Experience supporting production ML workloads.

Responsibilities

• Investigate current Azure ML development patterns and Data Scientist workflows.
• Analyse training pipelines, deployment pipelines, model artefacts, and monitoring capabilities.
• Document dependencies, integrations, and data flows.
• Extract and transition model assets, configurations, and deployment patterns.
• Support migration and testing of pilot models.
• Provide recommendations for migration and optimisation.

Skills

Azure ML

Python

ML frameworks

CI/CD

Model lifecycle management

Production ML workloads

Tools

Azure DevOps

Job description

Job Title: MLOps Engineer (Azure ML Specialist)
Rate: £438 Inside IR35
Duration: 6 months
Location: Hybrid - 3 Days Onsite in London per Week
Clearance: BPSS
Stages: 2 Stages

Purpose:

Assess and document the existing Azure ML estate and support migration of workloads.

Key Responsibilities

• Investigate current Azure ML development patterns and Data Scientist workflows.
• Analyse training pipelines, deployment pipelines, model artefacts, and monitoring capabilities.
• Document dependencies, integrations, and data flows.
• Extract and transition model assets, configurations, and deployment patterns.
• Support migration and testing of pilot models.
• Provide recommendations for migration and optimisation.

Key Experience

• Strong hands-on Azure ML experience.
• Python and machine learning frameworks.
• Azure DevOps, CI/CD, and model life cycle management.
• Experience supporting production ML workloads.