MLOps Engineer - Azure ML Specialist

Who is HelloKindred? HelloKindred are specialists in staffing marketing, creative and technology roles, offering a range of talent solutions that can be delivered on-site, remotely or hybrid. Our vision is to make work accessible and people’s lives better. We do this by disrupting traditional employment barriers – connecting ambitious talent to flexible opportunities with trusted brands.

Anticipated Contract End Date/Length: December 31, 2026 Work Set-Up: Hybrid (2–3 days per week in office) Clearance Required: BPSS Our client in the Information Technology and Services industry is looking for a MLOps Engineer

• Azure ML Specialist to assess and document the existing Azure ML estate and support the migration of machine learning workloads. The role will focus on investigating current Azure ML development patterns and Data Scientist workflows, analysing training and deployment pipelines, documenting dependencies and data flows, transitioning model assets and configurations, and supporting the migration and testing of pilot models.

What you will do

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 the migration and testing of pilot models.

Provide recommendations for migration and optimisation. Assess existing machine learning workloads and support production migration activities. Apply Azure DevOps and CI/CD practices to support model lifecycle management. Strong hands-on experience with Azure ML. Practical experience with Python and machine learning frameworks.

Experience working with Azure DevOps and CI/CD. Knowledge of model lifecycle management and MLOps practices. Experience supporting production machine learning workloads. Ability to investigate and document development patterns, pipelines, dependencies, integrations, and data flows. Experience supporting machine learning workload migration and testing.

Strong analytical skills with the ability to provide practical recommendations for migration and optimisation. Candidates must be legally authorized to live and work in the country where the position is based, without requiring employer sponsorship. HelloKindred is committed to fair, transparent, and inclusive hiring practices.

We assess candidates based on skills, experience, and role-related requirements. We appreciate your interest in this opportunity. While we review every application carefully, only candidates selected for an interview will be contacted. HelloKindred is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, colour, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic under applicable law.