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◆ 6/10
aitechOtherhybrid
About this role
Join GRI as an MLOps | DataOps professional to develop and maintain DWH infrastructure, CI/CD processes, and end-to-end ML pipelines in a hybrid/remote setup.
Description
Join GRI as an MLOps | DataOps professional to develop and maintain DWH infrastructure, CI/CD processes, and end-to-end ML pipelines in a hybrid/remote setup.
Responsibilities
Responsibilities
- Develop and maintain DWH infrastructure
- Build and enhance CI/CD processes for data and ML development
- Develop and maintain data processing and orchestration pipelines (Airflow)
- Implement end-to-end ML pipelines: from data collection to deployment and monitoring of models
- Design and develop MLOps platform (tool selection and integration)
- Deploy and maintain infrastructure for ML tasks: (JupyterHub + GPU, Airflow, ClickHouse, PostgreSQL, S3, etc.)
- Collaborate with ML and Data engineers to bring solutions to production
- Set up monitoring and alerting: data quality, pipeline stability, resources
- Automate routine tasks and develop self-service tools for the data team
Requirements
Requirements
- Confident experience with Docker and Kubernetes
- Experience with Airflow (or similar orchestration tools)
- Practical experience in building CI/CD for data/ML pipelines
- Good knowledge of Python, SQL, and Git
- Experience in deploying ML infrastructure (GPU clusters, storage, orchestration)
- Experience with cloud platforms
- Understanding of CI/CD principles and deployment automation
- Experience with APIs and understanding of high-load systems
- Experience with data streaming (Kafka / similar)
- Practical experience in setting up monitoring and logging
- Confident working in Linux
- A plus: Experience implementing experiment management systems (MLflow, ClearML)
Job Details
Market range (est.)$120k–$245k
LocationHybrid
AI Score★★★★★★☆☆☆☆ 6/10
PostedOct 1, 2026 (11d ago)
Tags & Skills
aitechOtherhybrid
Tech Stack
DockerKubernetesAirflowPythonSQLGitGPUCloud PlatformsAPIKafkaLinux