Job Description

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 at least one of the following languages:

English - Native of US or UK

Portuguese - Native of Brazil

Japanese - Native of Japan

Turkish- Native of Turkey

German - Native of Germany

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

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