DataOps Intern

About the Role
Join the Data Platform team at the company, where you will be immersed in an engineering role that carries real responsibilities. This internship is tailored for strong early-career engineers who have a solid foundation in Linux and cloud environments, along with practical experience using AI tools in their work. Interns will actively contribute to the production infrastructure that supports AI, ML, and data workloads by working on tasks under senior review. This is not a shadowing program but an opportunity to engage directly with critical systems in a fast-paced environment.

Key Responsibilities
Interns will engage in significant production tasks, including:

• Working with cloud infrastructure (primarily GCP) and the bare-metal fleet hosting data, ML, and AI workloads.
• Building and maintaining CI/CD pipelines for services and models.
• Running and troubleshooting containerized workloads on Kubernetes.
• Setting up and enhancing monitoring, alerting, and logging systems, and responding to alerts.
• Automating operational work using Python or Bash.
• Supporting model training and inference workloads, including environment setup, resource management, deployment, and cost-efficiency.
• Investigating incidents within infrastructure and pipelines to identify root causes of issues.
• Enhancing the reliability and cost efficiency of the platform.
• Operating within SAMA regulatory requirements, understanding the implications of data hosting and accessibility in Saudi fintech.

Technical Environment
While prior knowledge of the entire technology stack is not a prerequisite, familiarity with the following is beneficial:

• Data: CDC pipelines, BigQuery, Airflow
• ML: Airflow, ClearML, and similar orchestration tools
• AI: Bare-metal GPU servers, vLLM, open-source models served in-house
• Platform: GCP, Kubernetes, Linux, networking
• Context: Understanding SAMA regulations

Skills, Knowledge & Expertise
Candidates should possess:

• Solid Linux fundamentals, including filesystem management, processes, permissions, and networking basics.
• Hands-on experience with at least one cloud provider, preferably GCP, evidenced by personal projects or deployments.
• A fundamental understanding of networking including DNS, TCP/IP basics, and load balancing concepts.
• Working knowledge of containerization and Kubernetes—enough to deploy and debug workloads.
• Familiarity with monitoring and observability principles: metrics, logs, alerts.
• Proficiency in Python or Bash for automating tasks.
• Experience with Git and standard development workflows.
• Practical knowledge of AI tools used in personal projects, including the ability to discuss their applicability.
• Structured thinking and attention to detail, along with openness to constructive feedback.
• Proficient English communication for documentation and team interactions.

Additional Preferences
Candidates with the following experiences will be considered favorably:

• Infrastructure as code (Terraform or similar).
• Experience running CI/CD systems end-to-end (GitLab CI, GitHub Actions, etc.).
• Practical use of observability tools like Prometheus or Grafana.
• Exposure to MLOps tooling such as experiment tracking, model registries, feature stores, and inference serving.
• Experience attempting to run an open-source model independently on any platform.
• Familiarity with GPU workloads and understanding of cost implications.
• Interest in platform design and developer experience.

Eligibility

• Saudi nationals only.
• Open to both current students and recent graduates.
• Full-time engagement is expected, though students may coordinate class or exam schedules with their mentor in advance.

Job Benefits

• Duration: Six months, starting in autumn 2026.
• Paid internship funded by the company.
• Full integration into an engineering team.
• Opportunity to work within a distributed engineering team across multiple countries.
• Potential pathway to a junior role on the platform side after the internship, contingent upon performance.