Job Information
🌍 Location
Remote
Remote
💼 Experience
3+ Years
3+ Years
🤖 Domain
AI Quality Evaluation
AI Quality Evaluation
📊 Focus
LLM Assessment
LLM Assessment
Core Skills
LLM Evaluation
AI Testing
Content Review
Quality Audits
AI Performance Analysis
Prompt Evaluation
RLHF
ChatGPT
Claude
Gemini
AI Testing Areas
- AI Response Evaluation
- Hallucination Detection
- Bias & Safety Assessment
- Instruction Following Validation
- Regression Testing for AI Models
- Model Benchmarking
- Data Quality Validation
- Prompt Optimization
Key Responsibilities
- Review AI-generated responses for quality and accuracy.
- Evaluate outputs from LLMs, chatbots, and AI applications.
- Identify hallucinations, bias, safety issues, and inconsistencies.
- Conduct AI quality audits and testing activities.
- Analyze performance trends and quality gaps.
- Provide structured feedback to AI, product, and engineering teams.
Required Skills
- 3+ years in Quality Assurance, AI Evaluation, Content Review, or Data Quality.
- Understanding of Generative AI and Large Language Models.
- Strong analytical and critical thinking abilities.
- Excellent written and verbal communication skills.
- Experience evaluating content quality and compliance.
- Ability to work effectively in remote environments.
Why This Role Matters
AI Quality Analysts play a critical role in ensuring AI systems deliver accurate, reliable, and safe responses. By evaluating model outputs, identifying quality gaps, and providing structured feedback, they directly contribute to improving the performance and trustworthiness of modern AI applications.
Disclaimer: This job information is shared for career guidance purposes only. Applications are processed through the employer's official recruitment platform.