MLOps Engineer

Salary: £80,000 - 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 with a leading organisation on a high-profile AI initiative, seeking an experienced MLOps / Platform Engineer to 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 Data Science and Engineering teams to ensure robust infrastructure, seamless deployment pipelines, and high platform reliability. The role is 3 days per week onsite.

last updated 37 week of 2026