HLE Lead/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.
Craft high quality and informative content which can involve generating original content or curating existing content to be optimized for the LLM evaluation and training. This includes writing deep researched problems that currently best of models are not able to answer.
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:

Educational Background:
- Masters with distinction, or preferably PhDs with deep domain expertise in finance, engineering, physics, chemistry and medicine. A graduate degree is also preferred however with extensive experience in the respective field.
- Graduated from a top-tier US and international university or institute

Core Competencies & Skills:

Content Development:
- Expertise in developing high-quality, original problems in the following domains
- finance
- engineering
- science/ physics
- science/ chemistry
- science/ medicine

Exceptional Writing Proficiency: 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.
Originality and Creativity: The skill to generate unique ideas, and content that avoids mimicry of AI-generated content and showcases a distinct human voice.
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 Engineering: The skill to craft effective and precise prompts to elicit desired and high-quality outputs from LLM models, often described as essential for technical writers in an AI context.
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

Bottom-line: We are looking for young individuals who demonstrated consistent academic excellence with strong pedagogical expertise, who can work in a dynamic and fast paced work environment under minimal supervision