Research Intern (LLM)

Responsibilities

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  Design and construct high-quality, sufficiently challenging QA datasets (graduate/PhD level) inspired by GPQA, HLE, and AI4Sci families, collaborating with a global network of talented researchers.

  
  


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  Evaluate large language models on reasoning, factuality, and problem-solving benchmarks.

  
  


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  Develop review pipelines and quality-control criteria for expert-level question generation.

  
  


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  Analyze model outputs, conduct error taxonomy studies, and summarize insights for internal reports and research papers.

  
  


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  Collaborate with the 2077AI Foundation’s open-source benchmark teams on public dataset releases.

  
  

Qualifications

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  Strong background in computer science, data engineering, artificial intelligence, or related fields, with hands-on experience in large-scale data systems.

  
  


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  1+ years of experience with LLMs, prompt engineering, and evaluation frameworks (e.g., LM Eval Harness, OpenCompass).

  
  


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  Excellent written and verbal English skills and analytical reasoning.

  
  


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  Strong execution and team management skills—able to translate high-level objectives into actionable plans and drive team outcomes.

  
  


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  (Preferred) Experience with formal methods, chain-of-thought evaluation, or curriculum generation.

  
  


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  (Preferred) Relevant publications in top conferences.