Location
Remote (likely United States)
Employment
Contractor
First seen by Alion on Oct 16, 2026.
Overview
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micro1 is a US AI data company based in Miami that supplies frontier AI labs with expert-generated training data, model evaluations and reinforcement-learning environments, drawing on a network of vetted specialists. Its offerings include Intelligence Realm for frontier evaluations, Cortex for monitoring and improving agentic AI, and expert-demonstrated data for robotics labs, and it grew out of a service that matched companies with pre-vetted remote software developers. It recruits PhD and MSc domain experts in STEM, medicine, law and engineering as contract AI trainers, alongside software and ML engineers, attorneys, recruiters and partnership managers.
Backed by Antler, Activant Capital, 01 Advisors
Role Title: QA EngineerRole Type: ContractorLocation: 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.
- 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
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