Junior DevOps in Sber's RnD ML team: infrastructure support for ML services, CI/CD, Kubernetes, monitoring. Real production tasks with a mentor.
Tasks:
- Support and refine CI/CD pipelines in GitLab according to the team's existing templates.
- Deploy and update services in Kubernetes (Helm, manifests), assist with service publication.
- Connect services to monitoring and logging (Prometheus/Grafana, Vector → Elasticsearch), set up dashboards and alerts.
- Handle typical requests from related teams: access, quotas, diagnostics for "won't start / not writing logs / deployment failed".
- Write and update instructions in Confluence based on completed tasks.
- Gradually take tasks from the Jira backlog independently, discussing the results with the mentor.
Requirements:
- Linux at a confident user level: processes, network, permissions, systemd, reading logs.
- Basic understanding of Docker and Kubernetes: how a pod differs from a deployment, why a service is needed, how to check why a container crashed.
- Git and understanding of CI/CD pipelines (experience with GitLab CI is a plus).
- Bash and/or Python scripting at the level of "automating routine tasks".
- Basic understanding of HTTP, DNS, TLS.
Conditions:
- Comfortable modern office near Kutuzovskaya metro station.
- Hybrid work format.
- Annual salary review, annual bonus.
- Corporate gym and rest areas.
- Training system for professional and career development.
- Extended voluntary medical insurance policy from the first day of employment and insurance for family.
- Mortgage program for employees.
- Prime subscription with the possibility of sharing with three close contacts.
- Reward for recommending friends to the Sber team.
Skills:
- Linux
- Docker
- Kubernetes
- Git
- GitLab CI
- Bash
- Python
- HTTP
- DNS
- TLS
- Helm
- Prometheus
- Grafana
- Vector
- Elasticsearch
- Confluence
- Jira
