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OpenTrain AI is seeking about 65 QA Engineers for expert contract work on AI training and evaluation projects. Roles involve manual and automated testing, with emphasis on human data tasks such as RLHF and evaluation rating. The project spans 3–6 months with hourly rates between $90 and $175.
Applicants should have hands-on QA experience, clear communication of defects, and English proficiency. This contractor opportunity offers flexible engagement and alignment with ongoing AI research efforts.
OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is hiring and contracting experienced professionals for projects that help develop and evaluate next-generation artificial intelligence systems.
AI training is the human side of building artificial intelligence. Experts review model outputs, test proposed solutions, and provide structured feedback that helps AI systems become more accurate, reliable, and useful.
In this role, your practical software quality assurance knowledge will support evaluation rating, question answering, RLHF, and other human-data tasks. This work gives experienced QA professionals a direct way to contribute to how modern AI systems are built.
OpenTrain AI is seeking approximately 65 experienced QA Engineers to contribute to AI training and evaluation projects. The opportunity is intended for professionals with hands-on experience in manual or automated testing and prior experience with human data or AI-related projects.
The expected project duration is 3–6 months. Compensation is listed at $90–$175 per hour, with rates varying according to QA specialization, experience, and project requirements.
You will use your QA expertise to assess testing quality, analyze technical outputs, and provide clear feedback for AI training and evaluation workflows. Your work should reflect practical software testing standards and realistic expected behavior.
Applicants must have professional experience as a QA Engineer, Software Tester, Test Engineer, or in a similar role. Prior human data experience is mandatory, and candidates without this experience will not be considered.
You must be able to clearly explain testing decisions, defects, expected behavior, and the reasoning behind your evaluations. English proficiency must be at least B2 level, with fluent English specified for the opportunity.
This opportunity is suited to QA professionals who can combine rigorous testing practices with clear written evaluation. It is especially relevant if you have already worked on data labeling, annotation, AI/ML evaluation, RLHF, or other human-data projects.
Eligible applicants are located in the United States, United Kingdom, Finland, Netherlands, Ireland, India, Argentina, Belgium, Spain, Chile, Mexico, Australia, Austria, South Korea, Japan, Sri Lanka, Brazil, Canada, Colombia, Denmark, Egypt, France, Greece, Hungary, Iceland, Italy, Jordan, Monaco, Morocco, New Zealand, New Caledonia, the Philippines, Saudi Arabia, Eswatini, Sweden, Switzerland, Türkiye, the United Arab Emirates, or Vietnam.
Applicants move through a structured process designed to assess both general suitability and domain expertise before onboarding.
AI training and data labeling are rapidly growing ways to work in technology. People with software, language, analytical, and specialist expertise help prepare examples and review outputs that shape how AI systems behave.
As a QA Engineer, you can apply skills you already use in professional testing while contributing to cutting-edge AI development. Many AI training projects can also offer flexible participation, making the field compatible with other work or commitments.