MLOps/DevOps Engineer

We are looking for a Cloud/MLOps/DevOps Engineer or Architect to work across a variety of cloud infrastructure and machine learning deployment projects. The role involves building scalable environments, automating processes, and ensuring smooth integration and operation of systems in cloud platforms such as GCP and Azure.

Responsibilities:

• Design and maintain CI/CD pipelines for applications and ML models;
• Automate infrastructure deployment using Terraform or Pulumi;
• Manage containerized environments with Docker and Kubernetes;
• Support cloud migration processes (on-premise to Azure or GCP);
• Integrate and deploy ML models, including vLLM-based solutions;
• Set up monitoring and alerting with DataDog;
• Maintain version control using Atlassian Bitbucket;
• Ensure security, scalability, and high availability of infrastructure;
• Collaborate with developers, data scientists, and QA engineers;
• Provide architectural guidance and technical leadership when required.

Requirements:

• 5+ years in DevOps, cloud infrastructure, or system architecture;
• 3+ years of hands-on experience with GCP and/or Azure;
• 2+ years in cloud migration projects;
• 3+ years working with MLOps tools and workflows;
• Strong knowledge of Terraform, Docker, Kubernetes;
• Proficiency in Python and shell scripting;
• Experience with CI/CD automation and monitoring tools;
• Familiarity with DataDog, Bitbucket, and cloud-native architectures;
• Solid understanding of security and networking in cloud environments.

Nice to have:

• Experience with vLLM, MLflow, or Vertex AI;

• Programming skills in .NET, Java, Node.js, or Ruby;

• Previous work in consulting or customer-facing roles;

• Knowledge of the Atlassian stack (Jira, Confluence, Bitbucket);

Conditions:

• Official employment under the Labor Code of Kazakhstan;
• Remote format with an option to work from the office;
• International projects and team;
• Social package.