MLOps Engineer

Salary: £100,000 - 100,000 per year

Requirements:

• 5 years experience in Platform Engineering / DevOps
• Strong experience with AWS and cloud-native architectures
• Proven knowledge of CI/CD, automation, and DevOps best practices
• Experience with Kubernetes / containerisation technologies
• Strong programming skills (e.g. Python, Go, Node.js)
• Experience with observability tools (e.g. OpenTelemetry, Datadog)
• Understanding of security, performance optimisation, and scalability
• Experience working on AI / ML platforms or deployments
• Exposure to large-scale distributed systems
• AWS certifications

Responsibilities:

• Design, deploy, and manage AI platforms and agent infrastructure
• Build and maintain CI/CD pipelines and DevOps workflows
• Implement observability, monitoring, and logging solutions
• Optimise performance, scalability, and cost efficiency
• Support AI teams with infrastructure, deployment, and integration
• Ensure platform security, compliance, and high availability
• Automate infrastructure using Infrastructure as Code (IaC) tools
• Troubleshoot and resolve platform issues

Technologies:

• AI
• AWS
• CI/CD
• Cloud
• Datadog
• DevOps
• Support
• Kubernetes
• MLOps
• OpenTelemetry
• Python
• Security
• NodeJS

More:

We are partnering on a high-profile AI initiative and seeking an experienced MLOps / Platform Engineer to help us build and scale infrastructure supporting advanced AI solutions. You will play a key role in designing and operating a secure, scalable platform for deploying AI workloads and agents. Working closely with our Data Science and Engineering teams, you will help ensure robust infrastructure, seamless deployment pipelines, and high platform reliability. This role is based on-site three days per week.

last updated 39 week of 2026