❇️ **Release Engineer with MLOps function Senior **❇️ | Company: Top Selection

🔥 We are looking for** a Release Engineer with MLOps function for a project-based employment **

Grade: Senior Rate: from 288K to 315K Citizenship/Location: Russian Federation **Load: **full-time Term: long-term Contracting: only sole proprietorship ‼️

**Description: **We are creating an intelligent ML demand forecasting system that considers seasonality, promotions, macro- and microeconomic factors, customer behavior, and logistics constraints.

Our stack: GitHub/Gitlab, Jfrog Artifactory, SonarQube, Jenkins/GitlabCI , ArgoCD, Helm, Hashicorp Vault, OpenTelemetry, Grafana, Grafana Tempo, Mimir, Prometheus, Apache Spark, k8s

📝 Tasks:

• Facilitating and accelerating the work of developers
• Creating CI/CD pipelines.
• Assisting with application containerization, preparation for delivery and deployment.
• Technical consultation.
• Assisting in setting up a centralized development environment
• Managing the release process, conducting, and supporting releases.
• Submitting RFCs
• Conducting releases
• Monitoring system operability before, during, and after releases.
• Updating technical documentation.
• Infrastructure management
• Maintaining the operability of infrastructure services.
• Configuring service monitoring.
• Monitoring resource utilization, improving their efficiency.
• Timely updating of services and dependencies.
• Timely fixing of detected vulnerabilities in the source code and controlled services.

✅Candidate Requirements (+/-):

• At least 4 years in a DevOps/Release Engineer role or similar, with a focus on CI/CD and the release process.
• Experience working on projects with ML models.
• Successful release execution in production environments, including RFC management and monitoring system operability before/during/after releases.

✅Technical Skills and Responsibilities:

• CI/CD and Release Management: Creating and supporting pipelines in Jenkins/GitLab CI; managing the release process with ArgoCD and Helm; containerizing applications (Docker/Kubernetes).
• Infrastructure as Code: Working with Kubernetes (k8s), HashiCorp Vault for secrets; configuring and supporting infrastructure.
• Monitoring and Observability: OpenTelemetry, Grafana (Tempo, Mimir), Prometheus; monitoring resource utilization, identifying vulnerabilities (SonarQube).
• Artifacts and Repositories: GitHub/GitLab, JFrog Artifactory.
• MLOps Specifics: Experience with Apache Spark for ML workloads; automating ML model deployment, integration with ML pipelines.
• Additional: Documentation updates, technical consultations for developers, setting up a centralized dev environment, fixing vulnerabilities, and updating dependencies.

✅Technology Stack (required experience):

• GitHub/GitLab, JFrog Artifactory, SonarQube, Jenkins/GitLab CI.
• ArgoCD, Helm, HashiCorp Vault.
• OpenTelemetry, Grafana, Grafana Tempo, Mimir, Prometheus.
• Apache Spark, Kubernetes (k8s).