متدرب DataOps (DataOps Intern)

Job Summary

The DataOps Intern will work within Tabby’s Data Platform team to manage and improve the infrastructure supporting AI, ML, and data workloads. This role involves hands-on engineering tasks in cloud and bare-metal environments, focusing on reliability, cost efficiency, and regulatory compliance.

Responsibilities

• Manage cloud infrastructure primarily on GCP and bare-metal servers hosting data, ML, and AI workloads.
• Develop and maintain CI/CD pipelines for services and machine learning models.
• Operate and troubleshoot containerized applications on Kubernetes.
• Implement and enhance monitoring, alerting, and logging systems and respond to their outputs.
• Automate repetitive operational tasks using Python or Bash scripting.
• Support environments, resources, deployment, and cost management for model training and inference.
• Investigate infrastructure and pipeline incidents to identify root causes.
• Enhance platform reliability and cost efficiency while adhering to SAMA regulatory requirements.

Must haves

• Strong Linux fundamentals including filesystem, processes, permissions, and networking basics.
• Practical experience with at least one cloud provider; GCP experience is preferred but AWS or Azure is acceptable.
• Understanding of networking concepts such as DNS, TCP/IP, and load balancing.
• Working knowledge of containers and Kubernetes deployment and debugging.
• Familiarity with monitoring and observability concepts including metrics, logs, and alerts.
• Ability to automate operational tasks using Python or Bash.
• Experience with Git and standard development workflows.
• Active use of AI tools in engineering work with an informed perspective on model suitability.
• Structured thinking, attention to detail, openness to feedback, and English proficiency for documentation and communication.

Nice to haves

• Experience with infrastructure as code tools like Terraform.
• Experience managing CI/CD systems such as GitLab CI or GitHub Actions.
• Familiarity with observability tools like Prometheus and Grafana.
• Exposure to MLOps tooling including experiment tracking and model registries.
• Experience running open-source models and understanding of LLM operations.
• Experience with GPU workloads and cost management.
• Interest in platform design and developer experience.

What the company offers

• Paid six-month internship starting autumn 2026.
• Full integration into a distributed engineering team.
• Opportunity for a junior role on the platform team after internship based on performance.

We refresh listings regularly, but some roles close early on the source platform.