QA Engineer (Remote-Worldwide)

micro1; United States; Remote; USD 34,000 - 69,000; Full time

Job summary

micro1 is seeking a remote QA Engineer contractor to contribute to an AI training project. You will apply your QA expertise to ensure high-quality, real-world inputs for next-generation AI systems, focusing on data integrity, annotation, and comprehensive model evaluation.

No prior AI experience is required; industry knowledge and quality assurance skills are essential to drive successful outcomes and continuous improvement.

Qualifications

• Hands-on expertise in software quality assurance with a strong understanding of test planning and defect reporting.
• Proficiency in English at B2 level or above for effective collaboration and reporting.

Responsibilities

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

Skills

QA testing

Test planning

Defect reporting

English B2+

Job description

Role Type: ContractorLocation: Remotemicro1 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. Proficiency in English at B2 level or above for effective collaboration and reporting.