Hybrid AI Platform Engineer — MLOps/DevOps

DGH Recruitment Ltd

City Of London

On-site

GBP 70,000 - 110,000

Part time

14 days+
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Job summary

DGH Recruitment Ltd is seeking an experienced MLOps Engineer to design and operate a secure, scalable AI platform. You will collaborate with data science and engineering teams to deploy AI workloads and ensure reliable infrastructure.

The role focuses on building CI/CD pipelines, observability, and IaC automation, while optimizing performance and cost. You will ensure security and high availability for production systems.

Qualifications

  • 5+ years in Platform Engineering or DevOps roles.
  • Strong AWS experience and cloud-native architectures.
  • Proficient CI/CD, automation, and DevOps practices.
  • Experience with Kubernetes and containerisation technologies.
  • Programming skills (Python, Go, Node.js).
  • Familiarity with observability tools like Datadog/OpenTelemetry.
  • Understanding of security, performance, and scalability.

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.
  • Optimize 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.

Skills

Platform Engineering
AWS
CI/CD
Kubernetes
Python

Tools

Kubernetes
Datadog
OpenTelemetry
Terraform

Job description

DGH Recruitment Ltd is seeking an experienced MLOps Engineer to design and operate a secure, scalable AI platform. You will collaborate with data science and engineering teams to deploy AI workloads and ensure reliable infrastructure.

The role focuses on building CI/CD pipelines, observability, and IaC automation, while optimizing performance and cost. You will ensure security and high availability for production systems.

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