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.