Job Title: Query Vetting Specialist (GenAI)
Mode of work: India - Remote
Contract Duration: Depends on the Project
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.
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.
