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Generative AI Analyst

Posted 2 Days Ago
In-Office or Remote
18 Locations
Entry level
In-Office or Remote
18 Locations
Entry level
Develops and maintains prompts, responses, guidelines, and datasets for generative AI and large language model tools. Leads labeling initiatives with internal teams and third-party firms, trains stakeholders on LLM and dataset best practices, and supports quality assurance and testing. Requires native-level English, bilingual ability in a specified language, specialized domain knowledge, and a college degree or equivalent experience.
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Job Responsibilities:

The Generative AI Analyst role focuses on creatively developing and maintaining prompts, responses, and datasets to support cutting-edge machine learning tools and large language models (LLMs). This position involves collaboration with internal teams and third-party firms, contributing to labeling initiatives, and training teams on best practices for LLM development.

Responsibilities:

  • Creatively write prompts and responses across a diverse range of topics.
  • Lead labeling initiatives with third-party firms and internal customers.
  • Develop and update detailed guidelines and specifications for stakeholders.
  • Train teams on best practices for creating large language models and datasets.

Additional Job Details:

Requirements:

  • Native-level English proficiency with excellent written and verbal communication skills.
  • Bilingual proficiency in one or more of the following languages: Korean, Japanese, Mandarin, Spanish, German, or French.
  • Self-driven, motivated, and enthusiastic about working on state-of-the-art machine learning tools.
  • Domain knowledge in any specialized field (e.g., Finance, STEM).
  • 4-year accredited college degree or equivalent experience.

Ways to Stand Out:

  • College degree or experience in Linguistics, English Literature, Creative Writing, Journalism, or relevant domain knowledge (e.g., Law, Medical, Math, Coding).
  • Strong understanding of large language models and reinforcement learning from human feedback (RLHF).
  • Experience in labeling and tagging prompts/tasks for deep neural networks (DNN).
  • QA/testing experience.
  • Basic Python scripting skills.

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