AI Evaluation Specialist
Job Description
Job Title: AI Evaluation Specialist
Job Type: Contractor
Location: Remote
Job Summary: 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.
Key Responsibilities:
Design and implement self-contained evaluation tasks, including prompts, supporting files, and detailed grading rubrics to assess AI performance on practical computer-based workflows.
Define clear, unambiguous written criteria for what constitutes successful and unsuccessful task completion across diverse administrative and workflow scenarios.
Meticulously observe and document AI agent behaviors, producing crisp, precise summaries and reports in high-quality English.
Iterate and refine evaluation tasks and rubrics based on feedback and team collaboration to ensure robust benchmarking methodologies.
Work cross-functionally across a wide range of domains, adapting evaluation frameworks as project requirements evolve.
Collaborate with the customer's team to share insights and help drive continuous improvement in AI evaluation techniques.
Champion meticulousness, structured observation, and clear written communication throughout all project deliverables.
Required Skills and Qualifications:
Minimum 3 years of experience in roles emphasizing written precision and structured thinking—such as paralegal, executive assistant, junior analyst, librarian, document archival specialist, research assistant, technical writer, QA analyst, etc.
Native or fluent in English writing, with a demonstrated ability to produce observations that are succinct, specific, and unambiguous.
Proven skill in designing or applying rubric-based evaluation, grading against set criteria, or building structured scoring frameworks.
High attention to detail and ability to notice subtle patterns or inconsistencies others might miss.
Exceptional written and verbal communication skills, especially for documenting nuanced observations and feedback.
Fluency in navigating computers, common SaaS tools, web browsers, file management, and document editing platforms.
Strong self-direction, with the ability to independently take ownership of ambiguous or loosely defined projects.
Preferred Qualifications:
Prior experience evaluating AI outputs or participating in technology-driven process improvement projects.
Background in developing or refining evaluation rubrics or scoring methodologies.
Comfort working across multiple domains and adapting quickly to new types of workflow challenges.
About Micro1
Micro1 is building the essential infrastructure for the next generation of artificial intelligence, moving beyond the limitations of static datasets to create a dynamic ecosystem where models truly learn to think and act. At its core, the company understands that the path to frontier intelligence isn't paved with synthetic data alone; it requires the nuance, judgment, and contextual awareness that only expert human guidance can provide. By positioning itself at the intersection of human expertise and advanced reinforcement learning, Micro1 is tackling the hardest problem in AI today: teaching models not just to answer questions, but to reason through complexity and take meaningful actions in unpredictable, real-world environments.
This mission comes to life through Realm, Micro1's flagship training environment. Realm functions as a high-fidelity simulation ground where AI agents are immersed in scenarios that closely mirror the messiness of actual human workflows. Rather than relying on abstract benchmarks, Realm forces models to engage in agentic actions, multi-step decisions, digital navigation, coding, and problem-solving that require genuine comprehension. It is within these realistic sandboxes that world-class human data is generated, creating a continuous feedback loop where expert annotators observe, correct, and guide model behavior. This process does more than just fine-tune outputs; it fundamentally elevates a model's underlying reasoning architecture, ensuring that the intelligence developed in training holds up when deployed into the wild.
But training is only half the equation. Micro1 recognizes that the true test of an AI system lies in its production performance, which is where Cortex enters the picture. Cortex is a contextual evaluation platform designed to move beyond superficial accuracy metrics and provide a granular, real-time view of how agents behave in live settings. It doesn't just flag errors; it surfaces the underlying context behind failures, revealing why an agent struggled with a particular user intent or environmental variable. This insight is invaluable for engineering teams, as it transforms evaluation from a passive checkpoint into an active improvement tool. With Cortex, companies can catch degradation early, understand the nuances of edge cases, and feed those learnings directly back into Realm for retraining, creating a virtuous cycle of continuous advancement.
Ultimately, Micro1 is not merely a data lab or an evaluation tool it is a comprehensive intelligence engine that connects the entire lifecycle of model development. From the expert human feedback that sharpens raw capability, to the realistic RL environments that forge robust agentic behavior, to the contextual oversight that ensures reliability in production, Micro1 provides the integrated foundation that AI labs and enterprises desperately need. As the industry races toward truly autonomous systems, Micro1 stands as the critical bridge between laboratory breakthroughs and dependable, real-world impact, ensuring that frontier models do not just perform well on paper, but deliver genuine value in the complex, dynamic world they are meant to serve.