MLOps Engineer

MLOps Engineer Position Description

At CGI, you will play a pivotal role in enabling the deployment and operation of advanced AI systems that support critical national security outcomes. Working within our Space, Defence and Intelligence business unit, you will help design and deliver secure, scalable machine learning platforms that power innovation across mission‑critical environments. We combine deep sector expertise with emerging technologies and collaborative delivery to create impactful solutions, giving you the opportunity to take ownership of complex challenges, contribute creative ideas, and grow within a supportive, expert‑led community.

The Space, Defence and Intelligence business unit in CGI is a true IT Systems Integrator. We work, build, and operate bespoke, technically complex, mission‑critical systems which help our clients keep us all safe and secure. We bring innovation to our clients using proven and emerging technologies, agile delivery processes and our deep expertise across the breadth of space, defence, intelligence, aerospace and maritime, all underpinned by our end‑to‑end cyber capability.

We work collaboratively with global technology companies, cutting‑edge SMEs and academia to deliver the optimal solution for each client.

We offer a competitive salary, excellent pension, private healthcare, and a share scheme (3.5% + 3.5% matching) which makes you a CGI Partner not just an employee. We are committed to inclusivity, building a genuinely diverse community of tech talent and inspiring everyone to pursue careers in our sector, including our Armed Forces, and are proud to hold a Gold Award in recognition of our support of the Armed Forces Corporate Covenant.

Join us and you’ll be part of an open, friendly community of experts.

Due to the secure nature of the programme, you will need to hold UK Security Clearance or be eligible to go through this clearance. This position will be based on a site near Gloucester 5 days a week.

• Design & Deliver secure, scalable MLOps platforms for production environments
• Build & Optimise air-gapped machine learning pipelines and workflows
• Deploy & Manage LLM inference clusters and AI model hosting platforms
• Implement & Enhance model lifecycle processes, including monitoring and retraining
• Develop & Automate infrastructure using Dev Sec Ops  principles and tooling
• Monitor & Improve system performance using observability tools and best practices
• Collaborate & Innovate with cross‑functional teams to deliver mission‑critical solutions

• Experience building and operating production‑grade machine learning platforms, with strong technical skills across software development, infrastructure, and cloud‑native tooling.
• Solid understanding of Linux environments and modern MLOps practices.
• Experience developing in Python for data or platform engineering.
• Strong proficiency in Linux systems and command‑line environments.
• Experience with MLOps tools such as MLflow, Kubeflow or Airflow.
• Familiarity with monitoring tools such as Prometheus or Grafana.
• Experience with containerisation and orchestration (Docker, Kubernetes, Terraform).
• Understanding of CI/CD pipelines and Dev Sec Ops  practices.
• Experience with platforms such as VMware, Open Shift or Open Stack (desirable).
• Exposure to AI/ML workloads, GPU environments, or secure/air‑gapped systems (advantageous).