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 life cycle 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.

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