Senior AI Trainer

micro1 is engaging Senior AI Trainers to collaborate on a customer-driven project enhancing AI system quality through expert-level model training and evaluation. In this role, you'll apply your generalist expertise and hands-on experience with AI products to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities:

• Evaluate the performance of AI chat and search tools under standardized, repeatable conditions.
• Apply detailed grading guidelines to accurately evaluate, rank, and annotate model responses, providing structured feedback that improves model performance.
• Write, refine, and stress-test prompts that probe model capabilities, ensuring coverage of diverse scenarios, edge cases, and user intents.
• Verify consistency and accuracy across evaluations, correcting discrepancies between ratings and the underlying rubric or guidelines.
• Utilize AI training tools and platforms to record findings and submit evaluation datasets in alignment with project standards and milestones.
• Collaborate with project trainers and contributors to resolve ambiguities, refine guidelines, and ensure evaluation consistency across the team.
• Participate in ongoing quality reviews, incorporating feedback to maintain rigorous training and annotation standards.

Required Skills and Qualifications:

• Exceptional attention to detail and accuracy in reviewing and evaluating AI-generated content.
• Strong written and verbal communication skills for effective collaboration, reporting, and timely updates on progress and challenges.
• Demonstrated time management and self-organization abilities for independent, remote project participation.
• Analytical and problem-solving mindset, with a proactive approach to resolving evaluation challenges.

Preferred Qualifications:

• Proven experience with AI model training, RLHF, data labeling, or similar data-centric evaluation projects.
• Familiarity with AI products and tools, including prompt engineering and understanding of model behaviors and limitations.
• Experience writing evaluation rubrics, grading model outputs, or reviewing AI responses for accuracy, helpfulness, and safety.
• Background in AI training, machine learning data preparation, or LLM-focused projects (strongly preferred).