Query Vetters

Raters for GenAI Data

Key Responsibilities:

• Engage with GEN AI researchers and engineers to understand data collection/evaluation requirements
• Expand high-level requirements into a detailed workflow and communicate the same to a larger team
• Execute very quickly on collection & evaluation workflows with minimal supervision
• Innovate on data collection workflows to determine the most efficient way of achieving the researcher/engineer’s goal
• Collaborate with peers & cross-functional stakeholders to achieve maximum data throughput with highest quality
• Conduct In-depth research using LLM models. Delve deep into specific domains to gather reliable and up-to-date information.
• Thoroughly evaluate content and provide detailed feedback to ensure high quality and informativeness. This includes assessing original and curated content for LLM evaluation and training, and judging model responses to complex, deeply researched problems that current models cannot yet answer correctly.
• Fact checking and accuracy verification (precision and recall). Meticulously verify the factual integrity of the content, ensuring accuracy and mitigating the risk of the LLM generating misinformation once trained with this data.

Required Qualifications & Experience:

• Language Proficiency: Candidates must demonstrate Native or Bilingual Proficiency or Full Professional Proficiency in reading and writing in Hindi - Native of India

• Educational Background:
• Graduate with distinction with deep cultural knowledge.
• Graduated from a top-tier US and international university or institute

Core Competencies & Skills:

• Exceptional Reading and Writing Proficiency in the target language: Mastery of grammar, syntax, style, and the ability to produce clear, concise, and engaging content across various formats (articles, blogs, technical documentation).
• Strong Research and Fact-Checking: Ability to conduct in-depth research, identify credible sources, and meticulously verify information for accuracy and to mitigate biases.
• Attention to Detail: Precision in language, accuracy in data presentation, and thorough proofreading to deliver polished, error-free work.
• Communication Skills: Ability to articulate ideas clearly, actively listen, collaborate effectively with teams, and convey complex information to diverse audiences.
• Understanding of AI and LLMs: A foundational understanding of AI principles, machine learning, deep learning, natural language processing (NLP), and how LLMs work, including their capabilities and limitations.
• Prompt Review: Proficiency in identifying characteristics of effective and precise prompts that generate desired, high-quality outputs from LLM models.
• Familiarity with AI Tools: Experience using AI writing assistants and platforms to generate, refine, and optimize content.
• Ethical AI Awareness: Understanding potential biases in AI systems and the ethical implications of AI-generated content, with a focus on mitigating bias and promoting responsible use.
• Data Literacy: Ability to work with data, including understanding data collection, preparation, cleaning, and transformation for LLM training