MLOps Engineer / Machine Learning Engineer

MLOps Engineer / Machine Learning Engineer

Location: Portsmouth (2 days every other week on-site, remainder remote)

Rate: Up to £537 per day (Umbrella only)

Clearance: MOD SC Clearance required (enhanced vetting applies)

Your new company

You will be joining a leading global consultancy delivering critical digital transformation programmes within the public sector.

This role sits within a highly secure environment, supporting the development of advanced machine learning and MLOps capabilities across multiple use cases.

Your new role

As an MLOps Engineer, you will be responsible for developing and enhancing MLOps capabilities, enabling the deployment, scaling, and monitoring of machine learning solutions to secure and complex environments. You will work across engineering, DevOps, and data science teams to deliver robust, automated, and production-ready ML pipelines.

What you'll be doing

Develop and improve MLOps frameworks across multiple machine learning use cases
Build and maintain CI/CD pipelines using GitLab (YAML-based)
Deploy and manage containerised applications using Docker and Kubernetes
Implement DevSecOps practices, including security scanning and automated workflows
Develop scripts in Python, Bash, and Linux environments to support automation
Work within air-gapped environments, ensuring secure deployment of ML solutions
Collaborate with data scientists to operationalise ML models
Utilise tools such as MLflow and Airflow for model tracking and orchestration
Support cloud-based deployments across AWS and Google Cloud Platform
Ensure performance, reliability, and scalability of machine learning systems
What you'll need to succeed

Strong experience in MLOps or ML Engineering roles
Proven experience with Docker and Kubernetes (containerisation)
Hands-on experience with AWS and/or GCP cloud environments
Solid scripting skills in Python and Bash/Linux
Experience building CI/CD pipelines using GitLab (YAML)
Understanding of DevSecOps principles and tooling
Exposure to ML lifecycle tools such as MLflow and Airflow
Ability to work in highly secure or air-gapped environments
Strong problem-solving and collaboration skills
What you'll get in return

Opportunity to work on cutting-edge ML and AI initiatives
Exposure to secure government programmes and advanced environments
Competitive day rate up to £537 per day
Hybrid working model with flexibility
Long-term potential within a major consultancy client
Important information

SC Clearance is required (additional MOD vetting will apply and may extend onboarding timelines)
This role is PAYE via Umbrella only (inside IR35)
What you need to do now

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV.If this role isn't quite right for you, but you're exploring the market, please get in touch for a confidential discussion.

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