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Generative AI Analyst
California (Bay Area); Home Office (Michigan); Home office (North Dakota); Home Office (Indiana); Home office (Nebraska); Home office (Mississippi); Home office (Louisiana); Jupiter; Home Office (Missouri); Home Office (Nevada); Home office (West Virginia); Home office (Hawaii); Home office (Kentucky); Home Office (Burlingame); TX Field Office - Houston; Home Office (Kansas); Home Office (Iowa); Home Office (Belmont); Home Office (Oklahoma); MA Field Office; Home Office (Idaho); Home Office (Arkansas); VLCM; Home office (American Samoa); US (remote); Home office (Alaska); US (remote); Los Angeles; North Carolina - Remote; Home office (New Jersey); Home office (Colorado); US (remote); Montana (remote); Rhode Island (remote); US (remote); US (remote); US (remote); CA Client Field Office (San Fran Bay Area); San Francisco CA Bay Area; Home Office (CA Los Angeles); Home Office (Alabama); US (remote); US (remote); US (remote); US (remote); US (remote); US (remote); Houston, Texas; Portland, Oregon; Home Office (DC); US (remote); Home Office (New Hampshire); New York, New York; US (remote); CA Client Location (SF); Frederick, Maryland; Boston, Massachusetts; Chicago, Illinois; US (remote); US (remote); California (Bay Area); US (remote); Austin, Texas; PDX Testing Lab; Portland, Oregon; New York, New York; Frederick, Maryland; Home Office (South Carolina); Chicago, Illinois; Home Office (South Dakota); Boston, Massachusetts; California (Bay Area); California (Bay Area); Home Office (Tennessee)Posted 1 weeks ago
remotemid
Job Description
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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.