Computer Science AI Quality Assurance Lead

The work

You will review AI-generated technical content and trainer or QA work. This includes explanations, code, troubleshooting guidance, system design, database guidance, networking answers, and security-related material.

You will check whether content is technically correct, logically sound, clear, well documented, secure, and aligned with project rubrics. You will also give written feedback, identify repeated quality issues, answer technical questions, support onboarding and training, update guidelines, and maintain quality documentation.

You will help improve review workflows for remote technical teams and flag recommendations that are misleading, insecure, outdated, incomplete, or technically unsafe.

• Review technical AI content for correctness, clarity, terminology, formatting, instruction following, and rubric compliance.
• Evaluate programming, systems, databases, networking, cloud, APIs, debugging, and troubleshooting content.
• Provide precise feedback and communicate guideline updates.
• Support onboarding, training, technical questions, style guides, and review documentation.

What it pays and takes

This is a remote, hourly contractor role supporting technical AI training quality workflows. The role is listed as entry level, but the description requires substantial technical knowledge and at least three years of relevant experience.

• Pay: Up to $20 per hour.
• Schedule: Part-time, with a requirement of 20 or more hours per week.
• Location: India.
• Language: Strong English communication skills.
• Education: A bachelor's or master's degree, or equivalent professional experience, in computer science, information technology, software engineering, information systems, cybersecurity, data science, or a related technical field.
• Experience: At least three years in software development, IT support, systems administration, networking, cybersecurity, data workflows, technical education, technical writing, QA, or related technical review.
• Knowledge: Programming, algorithms, data structures, operating systems, databases, networking, cloud basics, security, APIs, debugging, and troubleshooting.
• Preferred tools and experience: Git, IDEs, terminals, Linux, Windows, macOS, SQL, cloud platforms, REST APIs, Docker, networking tools, support systems, remote technical teams, and review documentation.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind systems that generate and understand text, code, images, and other content. Reviewers assess examples, correct errors, and explain what good output looks like so AI systems can improve.