← Back to jobs
Himalayas · Partner listing

QA Engineer

micro1

⌖ WorldwideSalary not providedRemoteContract · Not specified

Source: Himalayas ↗

Location & working arrangement

Working arrangement is supplied by the provider. Check the original advert for attendance and travel requirements.

Provider location / applicant eligibility: Worldwide

About the role

Role Title: QA Engineer Role Type: Contractor Location: Remote 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 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. Preferred Qualifications Hands-on expertise in software quality assurance, with a strong understanding of test planning and defect reporting. Prior experience with data labeling, annotation, reinforcement learning from human feedback (RLHF), or model evaluation. Proficiency in English at B2 level or above for effective collaboration and reporting. Originally posted on Himalayas

Skills mentioned in the listing

Machine learningQuality assurance

Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.

Why these skills appear

Machine learning · mentioned
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 patte

Quality assurance · mentioned
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 eva