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QA Engineer

$63–120/hr · micro1 · remote

Open to people living anywhere except 21 places, per micro1's own policy (checked 9 Oct 2026). This listing doesn't name countries itself.

The 21 places micro1 leaves out

Afghanistan, Belarus, China, Cuba, Democratic Republic of the Congo, Hong Kong, Iran, Iraq, Libya, Macao, Myanmar, North Korea, Russia, Somalia, South Sudan, Sudan, Syria, Venezuela, Ukraine, Yemen, Ethiopia.

Check history

CheckedStatusSlots leftChangeHow
17 Oct 2026Open120–Script, platform’s board

The script reads the platform’s own job board every night. A job not confirmed for 10 days comes off the list.

Most people who don't get in fail the screening, not the CV. Five minutes here first: How to pass the micro1 AI interview with Zara.

What the work is

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.

Who gets hired

  • 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.

The platform posted this on 16 Oct 2026.

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