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- Tasks: Evaluate and enhance multilingual datasets for large language models, focusing on cultural nuances.
- Company: Join a forward-thinking team dedicated to improving AI language understanding.
- Benefits: Flexible working hours and the chance to work remotely while making an impact.
- Why this job: Be part of a mission to ensure AI respects cultural diversity and accuracy.
- Qualifications: Native English speaker with a Master's degree and experience in LLM evaluation preferred.
- Other info: Engage 25 to 30 hours per week in a dynamic and innovative environment.
We are looking for linguistically and culturally aware professionals to support the evaluation and enhancement of multilingual prompt-response datasets for large language models (LLMs). This role involves rubric design, evaluation of translations and model outputs, prompt creation, and red teaming focused on identifying and surfacing cultural nuances and biases in LLM behaviour.
Key Responsibilities:
- Rubric Definition & Prompt Evaluation
- Update rubric definitions with region/language-specific examples to ensure cultural and linguistic relevance.
- Identify the need for additional rubrics tailored to specific languages or regional contexts.
- Review prompts translated from English into the target language and revise where translations appear unnatural or inaccurate.
- Writing of thoughtful prompts which can test the cultural awareness of LLM models.
- Rate prompt-response pairs using a standardized evaluation template based on rubrics and provide detailed justifications to base the findings.
- Document problematic outputs and annotate them with clear explanations of rubric violations or cultural insensitivities.
Required Qualifications:
- Native proficiency in the target language (English) and deep familiarity with cultural norms in the corresponding region.
- Experience in LLM evaluation, content moderation, or linguistic QA preferred.
- Strong attention to detail with the ability to identify subtle issues in language use, tone, and cultural references.
- Comfortable working in spreadsheets and evaluation templates.
- Master’s degree in relevant stream.
Preferred Qualifications:
- Prior experience with prompt engineering or LLM testing.
- Familiarity with tools such as Gemini, ChatGPT or similar LLM platforms.
- Ability to clearly articulate reasoning behind rubric ratings or prompt edits.
Required Engagement: 25 to 30 hours per week.
Content Writer employer: Innodata Inc.
Contact Detail:
Innodata Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Content Writer
✨Tip Number 1
Familiarise yourself with the latest trends in LLM evaluation and cultural nuances. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of LLM evaluation and content moderation. Attend relevant webinars or join online forums where you can share insights and learn from others' experiences.
✨Tip Number 3
Prepare examples of your previous work that demonstrate your attention to detail and understanding of cultural contexts. Being able to discuss specific instances where you've identified biases or improved translations will set you apart.
✨Tip Number 4
Stay updated on the tools and platforms used in LLM testing, such as Gemini and ChatGPT. Familiarity with these tools will show your commitment to the role and your ability to hit the ground running.
We think you need these skills to ace Content Writer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Content Writer in the context of LLM evaluation. Familiarise yourself with rubric design, prompt creation, and cultural nuances to tailor your application effectively.
Highlight Relevant Experience: In your CV and cover letter, emphasise any experience you have in LLM evaluation, content moderation, or linguistic quality assurance. Be specific about your familiarity with cultural norms and how it relates to the role.
Craft a Tailored Cover Letter: Write a compelling cover letter that addresses the key qualifications listed in the job description. Use examples from your past work to demonstrate your attention to detail and ability to identify subtle language issues.
Proofread Your Application: Before submitting, carefully proofread your application materials. Ensure there are no grammatical errors or awkward phrasing, as this reflects your attention to detail and proficiency in English.
How to prepare for a job interview at Innodata Inc.
✨Showcase Your Linguistic Skills
As a Content Writer, it's crucial to demonstrate your native proficiency in English and your understanding of cultural nuances. Be prepared to discuss examples of how you've navigated language and culture in previous roles.
✨Familiarise Yourself with LLMs
Make sure you have a solid understanding of large language models and their evaluation processes. Research tools like Gemini and ChatGPT, and be ready to share your insights on how they can be improved or evaluated.
✨Prepare for Rubric Discussions
Since rubric design is a key responsibility, think about how you would approach creating or updating rubrics. Be ready to discuss specific examples of cultural or linguistic considerations that should be included.
✨Detail Orientation is Key
Highlight your attention to detail during the interview. Prepare to discuss instances where you identified subtle issues in language use or cultural references, as this will show your capability to handle the responsibilities of the role.
