In this hourly, remote contractor role, you will work as a Computer Science & IT Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across computer science, IT, software, systems, and technical AI training projects. You will review AI-generated computer science/IT content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for technical accuracy, conceptual correctness, code and systems reasoning, terminology quality, troubleshooting logic, security awareness, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires solid computer science/IT expertise, strong English communication skills, excellent attention to detail, structured communication,



and the ability to manage quality workflows across remote technical teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your computer science and IT quality leadership will directly help improve the world’s premier AI models by ensuring that technical training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations.

Key Responsibilities

Quality monitoring: Spot-check computer science and IT items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
Technical review: Evaluate AI-generated explanations, code snippets, troubleshooting steps, system-design content, database guidance, networking answers, security-related content, and technical reasoning f

📌 Computer Science (India)
🏢 SME Careers
📍 India