T
TensorGo
DevOps/ MLOps Intern
Skills
Google Cloud PlatformDockerCassandraKafkaGitLabJenkinsDatadogGrafanaAWSPrometheusGitHubLinuxKubernetesZabbixTerraformAzure
2 months ago
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Important information
Contract type:
Permanent
Location:
Hyderabad, Telangana, India
Work mode:
Onsite
Published on:
18 August 2026
What they need
- Profile
- The DevOps / MLOps Intern will support the development of scalable infrastructure, deployment pipelines, and cloud-native environments powering TensorGos products.
- This is a hands-on opportunity to work closely with the engineering team, gaining practical exposure to CI/CD, containerization, cloud deployment, and production operations.
- This role will be based in Hyderabad, work from office, for a duration of 6 months as an internship, with a potential PPO based on performance.
Requirements:
- Basic understanding of Linux systems, operations, and shell scripting.
- Familiarity with Docker, container networking, and cloud deployment concepts.
- Understanding of CI/CD workflows and application deployment pipelines.
- Knowledge of monitoring tools such as Prometheus, Grafana, Datadog, Nagios, or Zabbix.
- Awareness of cloud platforms such as AWS, GCP, Azure, or OCI.
- Passion for open-source technologies and infrastructure automation.
- Candidate of B.E / B.Tech in Computer Science, Electronics, Electrical, or any equivalent related discipline (pursuing or completed).
Good to have:
- Prior project work, coursework or internship exposure in DevOps, MLOps or cloud infrastructure.
- Familiarity with Kubernetes, Terraform, Jenkins, GitLab, GitHub Actions, or Argo CD.
- Exposure to open-source tools such as ELK, Kafka, or Cassandra.
Responsibilities:
- Convert software packages into Dockerfiles and containerized deployment artifacts.
- Support the implementation and maintenance of CI/CD pipelines and deployment workflows.
- Assist in monitoring, alerting, and infrastructure health tracking
- Help manage container-based environments and Kubernetes deployments.
- Install and troubleshoot open-source components in Docker and Kubernetes environments.
- Work with the engineering team on infrastructure automation, optimization, and operational improvements.
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