Evaluation Specialist/Recent Grad

What you would do

• Develop original questions across diverse subjects that probe AI reasoning depth and require multi-step analytical thinking
• Conduct thorough independent research, cross-checking multiple sources to ensure answer accuracy and comprehensiveness
• Formulate questions that demand synthesis and inference rather than simple information retrieval
• Test your work against AI models, evaluate responses, and iterate to refine difficulty and clarity
• Document research methodology, provide clear citations, and explain logical reasoning behind each answer

Who they want

• Demonstrated skill performing rigorous self-directed investigation and assessing source credibility systematically
• Meticulous care for accuracy and strong written command of English (fluency essential, native proficiency optional)
• Talent for crafting nuanced, well-structured questions that probe deep understanding
• Strong self-direction and reliability in independent remote work with accountability
• Welcoming applications from early-career professionals, PhD holders, and people with varied educational paths and experience

Main skills

What the interview asks about

1. 1.Source triangulation and fact verification

   AI systems learn from your answers; any factual error or unsupported claim contaminates the training data and degrades model quality downstream.

   For example: “You're researching a question about historical economic policy. Wikipedia says X, a journal article says Y, and a government archive says Z. How do you determine which is correct and how do you document your decision-making process?”

2. 2.Multi-step question design for reasoning

   AI models often excel at pattern matching but fail at genuine reasoning; your questions reveal where models actually understand versus memorize.

   For example: “Create a question requiring a model to compare two competing economic theories, identify assumptions in each, and predict which better explains a specific historical event. How do you structure this so a model must reason rather than retrieve?”

3. 3.Interpreting AI model failures

   When a model fails your question, you must diagnose whether it's a knowledge gap, reasoning error, or ambiguous wording in your question itself.

   For example: “A model misinterprets your question about climate mechanisms and conflates two distinct concepts in its answer. Is your question poorly worded, or does the model lack the reasoning to distinguish these concepts? How do you decide?”

4. 4.Ambiguity detection in question phrasing

   Ambiguous questions produce invalid results because you can't tell if the model failed at reasoning or just misread your intent.

   For example: “Your question asks about 'the impact of policy X on the economy.' A model answers narrowly about GDP while you intended a broader analysis of employment, inflation, and inequality. How do you revise the question to eliminate this ambiguity?”

5. 5.Difficulty calibration and iteration

   Questions too easy train models on trivial patterns; questions too hard become unsolvable. Your ability to calibrate difficulty ensures meaningful model training.

   For example: “You test your question and a baseline model solves it instantly, but advanced models only get 40% correct. What does that tell you about difficulty calibration, and how would you adjust?”

A task you may get

Develop a Q&A pair on an open research question: research with 3+ sources, write answer with citations, create multi-step question. Document your process.

How to prepare

• Study examples of open-ended research questions from academic journals and practice identifying which ones test reasoning versus recall
• Choose a complex topic (economics, history, science) and write a practice Q&A pair using source triangulation to verify accuracy
• Review several AI model responses to questions and practice diagnosing whether failures stem from knowledge gaps or reasoning lapses
• Draft three questions on the same topic at varying difficulty levels and explain your rationale for each level

The facts

Pay

$20–60/hr

Open to

Bangladesh, Hong Kong, India, Indonesia, Japan, Kazakhstan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Uzbekistan, Vietnam, Austria, Belarus, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Portugal, Russia, Spain, Switzerland, United Kingdom, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Algeria, Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Tunisia, United Arab Emirates, United States, Canada, Nigeria, Kenya, South Africa, Ghana, Ethiopia

Field

Generalist

Role type

Generalist

Posted

8/21/2026

Places left

5

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