AI Evaluation Assistant Job

We are looking for a detail-oriented and analytical AI Evaluation Assistant to support the testing, evaluation, and improvement of artificial intelligence systems. The successful candidate will review AI-generated responses, assess their accuracy and relevance, identify errors or inconsistencies, and provide structured feedback based on project-specific guidelines.

This role is ideal for individuals who enjoy working with AI tools, solving problems, analyzing information, and helping improve the quality and reliability of AI-generated outputs.

Evaluate AI-generated responses for accuracy, relevance, clarity, completeness, and logical consistency.
Review prompts, instructions, and reference answers to ensure they meet established quality standards.
Compare outputs from different AI models and identify strengths, weaknesses, and recurring errors.
Apply evaluation rubrics and scoring criteria consistently across assigned tasks.
Identify factual inaccuracies, reasoning errors, ambiguous instructions, and potential quality issues.
Document evaluation results and provide clear, constructive feedback.
Support the development and refinement of test cases, evaluation guidelines, and quality assurance procedures.
Maintain accurate task records and meet project deadlines.
Follow project-specific confidentiality, data-handling, and quality requirements.
Strong analytical thinking and attention to detail.
Good written English and the ability to communicate feedback clearly.
Ability to follow detailed instructions and apply evaluation criteria consistently.
Strong reading comprehension, critical thinking, and problem-solving skills.
Basic familiarity with AI tools such as ChatGPT, Claude, or Gemini.
Ability to work independently in a remote environment.
Reliable internet access and consistent availability for assigned tasks.
Experience in AI evaluation, data annotation, content review, software testing, research, or quality assurance.
Background in computer science, engineering, mathematics, data science, writing, or another relevant discipline.
Familiarity with prompt engineering, AI benchmarking, or evaluating model-generated content.
Programming experience in Python or another language for projects involving code evaluation.
Experience working with structured evaluation guidelines, scoring rubrics, or technical documentation.
Flexible remote working arrangements.
Opportunities to work on practical AI evaluation projects.
Exposure to emerging AI technologies and model improvement workflows.
Opportunities to develop expertise in AI quality assessment and benchmarking.
Compensation based on the agreed workload, project requirements, and experience.