DevOps Data Labeling - AI Training

Role Overview

We are collaborating with a research-driven AI organization developing next-generation models for technical reasoning and system operations. We’re seeking DevOps professionals with hands-on experience in command-line workflows, containerization, and infrastructure automation to contribute to the creation and evaluation of high-quality data used to train and refine AI systems.

This is an opportunity to leverage your technical expertise — working directly with advanced AI tools — to shape how machine learning models understand real-world DevOps, infrastructure management, and coding tasks.

Key Responsibilities

• Evaluate and annotate technical tasks and AI-generated code related to DevOps operations, scripting, and automation.
• Review, validate, and label scenarios involving Linux terminal commands, Python scripts, Dockerfiles, CI/CD pipelines, and system configuration files.
• Assess accuracy, efficiency, and safety of command-line operations and automation workflows.
• Collaborate with engineers and data scientists to refine labeling guidelines and ensure technical consistency.
• Provide feedback on model outputs, helping improve reliability and realism in DevOps reasoning tasks.

Ideal Qualifications

1+ year of hands-on experience in DevOps, site reliability engineering, systems administration, or infrastructure automation.
Proficient with Linux / UNIX command-line tools and scripting.
Experience using Python for automation, scripting, or tooling.
Comfortable working with Docker, containerization, and basic CI/CD concepts.
Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.
Strong attention to detail and ability to identify subtle technical inaccuracies or inefficiencies.
Excellent written communication and technical documentation skills.

Role Highlights

Flexible workload: 10–20 hours per week (with potential for expansion up to 40).
Fully remote and asynchronous — work from anywhere on your own schedule.
Opportunity to contribute directly to the next generation of AI models built for technical reasoning and automation.