QA Engineer – Remote (Worldwide)

IMPORTANT: after you apply, please check your email. We send you a link to complete your application — it is not considered until that last step is done. If you do not see it, check your spam folder.

This is a fully remote position, open to candidates based in 55 countries, including United States, United Kingdom, Canada, Germany, India, France, Netherlands, Singapore.

Pay: $63–$120/hr

Role Title: QA Engineer

Role Type: Contractor

Location: Remote

We are engaging QA Engineers to contribute to an AI training project with a forward-thinking customer. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is ideal for those passionate about quality assurance and eager to be at the forefront of AI innovation, with a focus on data integrity, annotation, and comprehensive model evaluation.

Scope of Work

1. Design, execute, and document test cases and scenarios to validate AI outputs against defined requirements.
2. Review, annotate, and label data sets to enhance machine learning model training accuracy.
3. Evaluate, analyze, and report on model predictions, identifying inconsistencies, errors, or patterns for continuous improvement.
4. Collaborate with cross-functional teams to communicate findings, raise questions, and clarify project requirements.
5. Contribute to the development and refinement of testing methodologies specific to AI-driven systems.
6. Maintain detailed, organized records of evaluations, test results, and feedback through written documentation.
7. Provide actionable recommendations to optimize data quality and model performance.

Preferred Qualifications

1. Hands-on expertise in software quality assurance, with a strong understanding of test planning and defect reporting.
2. Prior experience with data labeling, annotation, reinforcement learning from human feedback (RLHF), or model evaluation.
3. Proficiency in English at B2 level or above for effective collaboration and reporting.

How to apply

Apply here with your profile. We will then email you a link to complete your application on the hiring platform — your application is only considered once that final step is done.