DataOps

About the Internship

Tabby is offering a DataOps Internship for early-career engineers. This is an engineering role with real responsibilities, not a course or shadowing program. Interns will join the Data Platform team, working on production infrastructure under senior review, and are expected to meet engineering standards from day one.

The Data Platform Team

The Data Platform team manages the infrastructure that supports AI, ML, and data workloads at Tabby. This includes compute, orchestration, deployment, observability, and cost control across cloud environments. The work combines aspects of classic DevOps with machine learning operations, ensuring that clusters, pipelines, and monitoring support both service uptime and model training, serving, and measurement.

Key Responsibilities

• Work with cloud infrastructure, primarily GCP, and bare-metal fleets hosting data, ML, and AI workloads.
• Build and maintain CI/CD pipelines for services and models.
• Run and troubleshoot containerized workloads on Kubernetes.
• Set up and improve monitoring, alerting, and logging systems, and respond to their outputs.
• Automate repetitive operational tasks using Python or Bash.
• Support model training and inference workloads, including environments, resources, deployment, and cost management.
• Investigate incidents in infrastructure and pipelines to identify root causes.
• Improve the reliability and cost efficiency of the platform.
• Ensure compliance with SAMA regulatory requirements, particularly regarding data residency and access in Saudi fintech.

Qualifications and Requirements

• 0-1 years of experience.
• Comfortable working in Linux and cloud environments.
• Experience using AI tools in practical applications.

Internship Details

This is a paid, six-month internship scheduled to start in autumn 2026. Interns will be fully integrated into an engineering team. Tabby operates with a distributed engineering team across multiple countries. While not guaranteed, the intent is for successful interns to transition into a junior role on the platform team following the internship, dependent on performance.