# DevOps/MLOps InternHyderabad·0 to 1 year·DVOI252507·Posted on: Aug 22, 2026The DevOps / MLOps Intern will support the development of scalable infrastructure, deployment pipelines, and cloud-native environments powering TensorGo’s products.ProfileThe DevOps / MLOps Intern will support the development of scalable infrastructure, deployment pipelines, and cloud-native environments powering TensorGo’s 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.