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- Tasks: Design and operate secure AI platforms for critical national security projects.
- Company: Join CGI, a leader in tech solutions for defence and intelligence.
- Benefits: Enjoy a competitive salary, excellent pension, private healthcare, and share scheme.
- Why this job: Make a real impact on national security with cutting-edge AI technology.
- Qualifications: Experience in machine learning platforms and proficiency in Python required.
- Other info: Work on-site near Gloucester in a dynamic, mission-critical environment.
The predicted salary is between 60000 - 75000 ÂŁ per year.
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.
Due to the secure nature of the programme, you will need to hold UK Security Clearance or be eligible to undergo clearance. This position will be based on site near Gloucester five days a week.
Your future duties and responsibilities
- Design, build and operate secure AI and machine learning platforms within highly controlled environments.
- Develop the infrastructure and automation required to deploy, monitor and scale models in production, including large language models and other advanced AI systems.
- Deliver resilient, high‑performance platforms that enable critical decision‑making and operational effectiveness.
Key Responsibilities
- 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 DevSecOps principles and tooling.
- Monitor & improve system performance using observability tools and best practices.
- Collaborate & innovate with cross‑functional teams to deliver mission‑critical solutions.
Required qualifications
- Experience building and operating production‑grade machine learning platforms.
- Proficiency in Python for data or platform engineering.
- Strong command‑line skills in Linux systems.
- 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 DevSecOps practices.
- Experience with platforms such as VMware, OpenShift or OpenStack (desirable).
- Exposure to AI/ML workloads, GPU environments, or secure/air‑gapped systems (advantageous).
Benefits
- Competitive salary.
- Excellent pension scheme.
- Private healthcare.
- Share scheme (3.5% + 3.5% matching).
MLOps Engineer (SC Clearance) in Gloucester employer: CGI
Contact Detail:
CGI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer (SC Clearance) in Gloucester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving secure AI systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common MLOps scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace MLOps Engineer (SC Clearance) in Gloucester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the MLOps Engineer role. Highlight your experience with machine learning platforms and any relevant tools like MLflow or Kubeflow. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Don't forget to mention your understanding of secure environments and DevSecOps principles.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them! Whether it's building machine learning pipelines or deploying models, we love to see real-world examples of your work. It helps us understand your hands-on experience.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s straightforward and ensures your application goes directly to us. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at CGI
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, MLOps tools, and containerisation. Brush up on your command-line skills in Linux and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in building and operating machine learning platforms. Think about specific instances where you optimised workflows or improved system performance, as this will demonstrate your hands-on experience.
✨Understand the Security Aspect
Since this role requires UK Security Clearance, be prepared to discuss your understanding of secure environments and how you’ve worked within them. Highlight any experience with air-gapped systems or secure AI deployments to show you’re a good fit for the sensitive nature of the work.
✨Collaborate and Communicate
This position involves working closely with multidisciplinary teams, so be ready to talk about your collaboration experiences. Share how you’ve effectively communicated technical concepts to non-technical stakeholders, as this will showcase your ability to work in a team-oriented environment.