Develop and maintain prompts, responses, and datasets for large language models. Lead labeling initiatives with internal teams and third-party firms, create stakeholder guidelines, and train teams on LLM and dataset development best practices. The role requires native-level English, bilingual proficiency in an additional language, specialized domain knowledge, and a college degree or equivalent experience.
If you have a Candidate Login already, but have forgotten your password please use the steps to reset your password. If you have forgotten your email login, please contact [email protected] subject Workday Candidate Login
When creating your Workday account and entering personal information like name, address, please do not use ALL CAPS.
Thank you!
NOTICE: For Privacy Policy please review here
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.
WeLocalize New York, New York, USA Office
15 W 37th Street, 4th Floor, New York, NY, United States, 10018
Similar Jobs
Machine Learning • Natural Language Processing
Leads technical and writing teams delivering generative AI products. Coordinates customers, data, product, and research teams; tracks annotator metrics; creates prompts and responses; manages labeling initiatives; develops guidelines; trains stakeholders on LLM and dataset best practices; and supports quality assurance while handling potentially sensitive content.
Top Skills:
Deep Neural NetworksGenerative AiLarge Language ModelsPythonRlhf
Machine Learning • Natural Language Processing
Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.
Top Skills:
Deep Neural Networks (Dnns)Large Language Models (Llms)PythonReinforcement Learning From Human Feedback (Rlhf)
Artificial Intelligence • Machine Learning • Natural Language Processing • Professional Services
Review, evaluate, and validate AI-generated content (text, audio, images, video). Annotate and label data, identify errors and quality issues, compare outputs for accuracy, provide written justifications, follow project guidelines, complete tasks independently on schedule, and attend training and office hours.
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
