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Azure DevOps; MLOps Engineer - Lead

Job in Abu Dhabi, UAE/Dubai
Listing for: NorthBay Solutions LLC
Full Time position
Listed on 2025-12-02
Job specializations:
  • IT/Tech
    Cloud Computing, AI Engineer, Data Engineer, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Azure DevOps (MLOps) Engineer - Lead

About the Role:

North Bay is a leading AWS Premier Partner, is seeking a highly skilled
Lead
Dev Ops / MLOps Engineer (Azure, Terraform) to join their growing cloud and AI engineering team. This role is ideal for candidates with a strong foundation in cloud Dev Ops practices and a passion for implementing MLOps solutions at scale.

Key Responsibilities:
  • Design, implement, and manage CI/CD pipelines using tools such as Jenkins, Git Hub Actions, or Azure Dev Ops

  • Develop and maintain Infrastructure-as-Code using Terraform

  • Manage container orchestration environments using Kubernetes

  • Ensure cloud infrastructure is optimized, secure, and monitored effectively

  • Collaborate with data science teams to support ML model deployment and operationalization

  • Implement MLOps best practices
    , including model versioning, deployment strategies (e.g., blue-green), monitoring (data drift, concept drift), and experiment tracking (e.g., MLflow)

  • Build and maintain automated ML pipelines to streamline model lifecycle management

Required Skills:
  • 7+ years of experience in Dev Ops and/or MLOps roles

  • Proficient in CI/CD tools
    :
    Jenkins, Git Hub Actions, Azure Dev Ops

  • Strong expertise in Terraform and cloud-native infrastructure (AWS preferred)

  • Hands-on experience with Kubernetes
    , Docker, and microservices

  • Solid understanding of cloud networking, security, and monitoring

  • Scripting proficiency in Bash and Python

Preferred

Skills:

  • Experience with
    MLflow
    , TFX, Kubeflow, or Sage Maker Pipelines

  • Knowledge of model performance monitoring and ML system reliability

  • Familiarity with AWS MLOps stack or equivalent tools on Azure/GCP

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