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Scopic

Your Cost-effective, Cross-continental, Digital Innovation Partner

DevOps/MLOps Engineer

DevOps EngineerDevOps EngineerPart TimeRemoteSeniorTeam 201-500Since 2006H1B No SponsorCompany SiteLinkedIn

Location

Worldwide

Posted

2 days ago

Salary

0

Seniority

Senior

Job Description

DevOps/MLOps Engineer

Scopic

• Design and implement CI/CD pipelines for both general applications and machine learning workflows • Build and maintain scalable infrastructure using containerization (Docker, Kubernetes) and infrastructure-as-code tools • Manage and optimize cloud-based environments across AWS, GCP, or Azure • Deploy, monitor, and maintain machine learning models and pipelines in production environments • Establish and improve monitoring, logging, and alerting systems for application and ML infrastructure health • Automate deployment, scaling, and operational tasks to reduce manual overhead and improve reliability • Collaborate with software engineers and data scientists to understand deployment requirements and optimize system architecture • Ensure security, performance, and reliability across infrastructure and application layers • Troubleshoot and resolve infrastructure, deployment, and operational issues • Maintain documentation and best practices for infrastructure and deployment processes

Job Requirements

  • 3+ years of hands-on DevOps or infrastructure engineering experience
  • Strong proficiency with containerization and orchestration (Docker, Kubernetes)
  • Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Ansible
  • Solid understanding of CI/CD concepts and hands-on experience with tools like Jenkins, GitLab CI/CD, GitHub Actions, or similar
  • Strong programming skills in Python, Bash, or Go for automation and scripting
  • Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure)
  • Familiarity with monitoring and logging tools (Prometheus, ELK stack, CloudWatch, or similar)
  • Experience with ML operationalization and deployment platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI is a plus
  • Understanding of ML frameworks and workflows (TensorFlow, PyTorch, scikit-learn) is a plus
  • Strong problem-solving skills and ability to work independently on infrastructure challenges

Benefits

  • Paid training and other professional opportunities
  • Flexibility and freedom to work from anywhere with a stable internet connection
  • Consistent flow of engaging, challenging work to do
  • Annual pay increases for good performance

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