Software Test Engineer – Remote

YO AI Labs; New York (NY); Remote; USD 55,000 - 83,000; Full time

Job summary

YO AI Labs is seeking a detail-oriented QA Engineer for a remote contractor role to support AI training projects. You will validate AI outputs, review data annotations, and ensure data quality through rigorous testing and documentation.

The position emphasizes analytical thinking, strong English communication, and collaboration with cross-functional teams to improve model performance and testing methodologies.

Qualifications

• Experience in software testing and quality assurance.
• Understanding of test planning and defect reporting.
• Experience with data annotation, RLHF, or AI evaluation is preferred.
• Strong analytical, documentation, and communication skills.

Responsibilities

• Design and execute test cases to validate AI outputs.
• Review, annotate, and label datasets.
• Identify errors and inconsistencies in model predictions.
• Document test results and provide actionable feedback.
• Collaborate with teams to improve testing methodologies.
• Recommend improvements to data quality and model performance.

Skills

Software Quality Assurance

Test Planning and Test Case Design

Data Annotation and Labeling

AI Model Evaluation

Defect Reporting and Documentation

Data Quality and Validation

Analytical Thinking and Attention to D

English Communication (B2 or higher)

Job description

QA Engineer

Role Type: Contractor

Location: Remote

Job Description We are seeking detail-oriented QA Engineers to support an AI training project focused on quality assurance, data annotation, and AI model evaluation. Prior AI experience is not required.

Required Skills

• Software Quality Assurance
• Test Planning and Test Case Design
• Data Annotation and Labeling
• AI Model Evaluation
• Defect Reporting and Documentation
• Data Quality and Validation
• Analytical Thinking and Attention to Detail
• English Communication (B2 or higher)

Responsibilities

• Design and execute test cases to validate AI outputs.
• Review, annotate, and label datasets.
• Identify errors and inconsistencies in model predictions.
• Document test results and provide actionable feedback.
• Collaborate with teams to improve testing methodologies.
• Recommend improvements to data quality and model performance.

Qualifications

• Experience in software testing and quality assurance.
• Understanding of test planning and defect reporting.
• Experience with data annotation, RLHF, or AI evaluation is preferred.
• Strong analytical, documentation, and communication skills.