Role Overview

The AI Evaluation Analyst is responsible for assessing the quality, performance, and reliability of AI systems and model outputs. This role supports the development and continuous improvement of AI products by analyzing results, identifying patterns, and providing structured feedback to technical and cross functional teams.

Key Responsibilities

Review and evaluate AI generated outputs for accuracy, relevance, safety, and consistency
Apply predefined evaluation frameworks, rubrics, and quality standards
Conduct qualitative and quantitative analysis on model performance
Identify edge cases, failure patterns, and areas for improvement
Document findings clearly and provide actionable recommendations
Collaborate with data scientists, product teams, and engineers to refine models
Support testing cycles, experiments, and benchmarking initiatives
Maintain high attention to detail when handling sensitive or confidential data

Skills and Qualifications

Strong analytical and critical thinking skills
Ability to interpret guidelines and apply structured evaluation criteria
Excellent written communication and documentation abilities
Comfortable working with datasets, spreadsheets, and reporting tools
Familiarity with AI concepts such as machine learning, NLP, or large language models is a plus
Detail oriented, consistent, and able to manage repetitive review tasks
Ability to work independently while meeting quality and turnaround expectations

Preferred Background

Experience in quality assurance, data analysis, research, or content review
Exposure to AI products, prompt evaluation, model testing, or annotation workflows
Comfort working in fast evolving, experimentation driven environments

Toptal

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AI Evaluation Analyst