mlops engineer

Ameriabank CJSC operates in the finance, banking, and insurance industry.

• Design, deploy, and operate production Kubernetes clusters on-premises with a focus on high availability, scalability, and zero-downtime deployments;
• Manage Helm charts and ArgoCD for GitOps-based continuous delivery of platform and application workloads;
• Build and maintain CI/CD pipelines in Azure DevOps for automated testing and deployment across data and ML services;
• Architect and maintain a modern data lake using open table formats such as Iceberg on on-premises and hybrid storage;
• Build, schedule, and monitor scalable batch and streaming pipelines using Apache Airflow, Apache Spark, and Apache Flink;
• Deploy and operate Trino and ClickHouse as query engines for analytics over the data lake;
• Deploy and operate JupyterHub and Dagster on Kubernetes for ML experimentation and workflow orchestration;
• Manage the Feature Store using Feast and PostgreSQL, along with Parquet-based data storage for ML workloads;
• Work closely with Data Science and Data Engineering teams to productionize ML workflows and onboard new data sources.

• Hands-on experience designing and managing Kubernetes clusters from scratch; on-premises experience is preferred;
• Hands-on experience with Helm and ArgoCD for GitOps-based application delivery in Kubernetes environments;
• Experience building CI/CD pipelines with Azure DevOps;
• Experience with Apache Airflow, Apache Spark, and Apache Flink for pipeline orchestration and processing;
• Experience with Trino or ClickHouse as distributed query engines;
• Experience with dbt for data transformation and modeling;
• Familiarity with modern open table formats such as Iceberg;
• Nice to have: familiarity with Dagster, JupyterHub, Feast, or Parquet-based data lake patterns.

• No conditions specified