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Northbay

Azure DevOps (MLOps) Engineer - Lead

Job Posted 6 Days Ago Reposted 6 Days Ago
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India
Senior level
India
Senior level
Lead engineering team in designing and managing CI/CD pipelines, MLOps solutions, and infrastructure using tools like Terraform and Kubernetes.
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Job Title: Azure DevOps Engineer (MLOps) - Lead
Location: Onsite in UAE office for 2-3 months initially, and then remote from India
Employment Type: Full-time
Note: This role requires flexibility to travel to AbuDhabi office for initial 2 to 3 months, and then remote from India

About the Role:

NorthBay is a leading AWS Premier Partner, is seeking a highly skilled Lead DevOps / 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 DevOps practices and a passion for implementing MLOps solutions at scale.

Key Responsibilities:
  • Design, implement, and manage CI/CD pipelines using tools such as Jenkins, GitHub Actions, or Azure DevOps

  • 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 DevOps and/or MLOps roles

  • Proficient in CI/CD tools: Jenkins, GitHub Actions, Azure DevOps

  • 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 SageMaker Pipelines

  • Knowledge of model performance monitoring and ML system reliability

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

Top Skills

Azure Devops
Docker
Github Actions
Jenkins
Kubeflow
Kubernetes
Mlflow
Sagemaker
Terraform
Tfx

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