QA Engineer - Remote

Required Skills software quality assurance test case design test execution defect reporting data annotation data labeling ai model evaluation documentation english communication cross-functional collaboration micro1 is engaging QA Engineers to contribute to an AI training project with a forward-thinking customer. 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.

Role Title: QA Engineer

Role Type: Contractor

Location: Remote

Required Skills

micro1 is 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.