Toptal is a highly selective global network of elite professionals, including software engineers, designers, marketing specialists, management consultants, product managers, and project managers. Leading companies rely on Toptal to source top-tier talent for their most critical initiatives.

Role Overview

The AI Evaluation Analyst is responsible for reviewing the quality, performance, and reliability of AI systems and their outputs. This role plays a key part in the ongoing development and improvement of AI products by analyzing results, spotting trends, and delivering structured feedback to both technical and cross-functional teams.

Key Responsibilities

• Assess AI-generated content for accuracy, relevance, safety, and consistency.
•  Apply established evaluation frameworks, scoring rubrics, and quality benchmarks.
•  Perform both qualitative and quantitative analysis of model outputs and performance.
•  Identify edge cases, recurring failure patterns, and areas that require improvement.
•  Document findings clearly and provide practical, actionable recommendations.
•  Work closely with data scientists, engineers, and product teams to refine models and workflows.
•  Support testing cycles, experiments, and benchmarking efforts.
•  Handle sensitive or confidential data with care and attention to detail.

Skills and Qualifications

• Strong analytical and critical thinking abilities.
•  Ability to interpret guidelines and consistently apply structured evaluation criteria.
•  Excellent written communication and documentation skills.
•  Comfortable working with datasets, spreadsheets, and reporting tools.
•  Basic understanding of AI concepts such as machine learning, NLP, or large language models is a plus.
•  Highly detail-oriented with the ability to manage repetitive review tasks accurately.
•  Capable of working independently while meeting quality standards and turnaround times.

Preferred Background

• Experience in quality assurance, data analysis, research, or content review roles.
•  Exposure to AI products, prompt evaluation, model testing, or data annotation workflows.
•  Comfort working in fast-paced, experimental, and rapidly evolving environments.