Micro1 review · AI Training & Data Labeling
QA Engineer — AI Model Evaluation & Annotation (micro1)
What the work involves
micro1 is engaging QA Engineers for an AI training project with a forward-thinking customer, helping train next-generation AI systems through high-quality real-world input. The role blends traditional quality assurance with AI data work: you design, execute and document test cases and scenarios that validate AI outputs against defined requirements, review, annotate and label datasets to sharpen model training, and evaluate and report on model predictions — identifying the inconsistencies, errors and patterns that drive improvement. You'll collaborate with cross-functional teams to communicate findings and clarify requirements, help develop testing methodologies specific to AI-driven systems, keep detailed records of evaluations and results, and recommend ways to improve data quality and model performance.
Contractor role, fully remote. No prior AI experience is required — your domain knowledge is what matters.
What you'll do
- Design, execute and document test cases and scenarios that validate AI outputs against defined requirements
- Review, annotate and label datasets to improve machine learning model training accuracy
- Evaluate, analyze and report on model predictions, identifying inconsistencies, errors and patterns
- Collaborate with cross-functional teams to communicate findings and clarify project requirements
- Help develop and refine testing methodologies specific to AI-driven systems
- Maintain detailed, organized records of evaluations, test results and feedback
Requirements & eligibility
- Hands-on expertise in software quality assurance, with strong test planning and defect reporting
- Prior experience with data labelling, annotation, RLHF or model evaluation
- English proficiency at B2 level or above
- Able to work independently and document evaluations in detail
- Remote (no country restriction stated in the posting)
How to apply
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