AI Analyst – FRENCH Speaker - Cpl Healthcare
  • Dublin, Leinster, Ireland
  • via BeBee.com
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Job Description

AI Analyst – FRENCH Speaker – Office Based – Dublin


Global Talent on behalf of our Enterprise Tech client have a requirement for an AI Analyst - FRENCH speaker to join their team.

This post is PERMANENT position. The role is based in Dublin. The working model is onsite.


Working a 40 hours per week the successful candidate will be employed as a permanent member of team and will be paid a fix rate plus bonus.


Notes that all applicants must belegible to work in Ireland and resident in Dublin region to be considered for this position.


Salary:
€ Bonus. (25% increasing pay from 22:00 to 02:00)


IMPORTANT:

We can process only candidates eligible to work in Ireland full-time (EU passport, Stamp 4, Stamp 1G for at least 12 months, Access to Labour Market).

Thank you for understanding.


Summary of Role:
Are you Brave, Wise, Proud, and ready to Exceed? Are you passionate, driven to reach goals and objectives, have excellent attention to details, and have experience in a client-focused environment?

Job Description


As a Generative AI Annotator, your role will be to create, assess, and refine pairs of questions and answers to improve a large language model (LLM).

You'll generate realistic questions that someone might ask the LLM in a real-life context and provide the best possible answer.

This task will involve you reviewing a set of guidelines, creating sample prompts and responses in your area of expertise.

Duties and Responsibilities


  • Annotate English data accurately and consistently, in accordance with predefined annotation guidelines.
  • Evaluate the quality of existing data resources, as well as the output of machine learning classifiers and internal tools.
  • Develop, implement, and maintain guidelines and procedures for consistent, high-quality classification, and content creation and organization.
  • Perform basic research as needed to annotate accurately.
  • Provide feedback on the annotation tasks and contribute to the continuous improvement of the data annotation process.
  • Provide insights regarding observed patterns in the annotated data.
  • Research new entity categories and best practices for organizing them.
Candidate Profile


The ideal candidate has previous experience in effectively coping with a fast-paced, high-pressure role in a constantly changing business environment.

They will be client-oriented, enthusiastic, courteous, assertive, and motivated to take charge of the development and improvement of LLM (large language models).

Essential Competencies


  • High Proficiency in English – C1 Level minimum as per the CEFR.
  • Educational background, undergraduate university degree. Diverse representation across a domain required by the business and listed in the job advertisement is necessary.
  • Understanding of common social norms (Social dynamics, social media, popular culture).
Other Competencies


  • Ability to reference online resources, rephrase and write cohesive, accurate, responsive, and sometimes empathetic answers to the prompts in the perspective of a LLM.
  • Ability to ask and/or answer specialized domain free-form prompts at university-level difficulty.
  • Experience in data and trend analysis, and insights.
  • Experience in developing and implementing a range of initiatives.
  • Experience working in a constantly changing environment.
  • Able to work independently and collaboratively; must be able to manage multiple activities simultaneously and execute decisions with judgment and discretion.
  • Strong performance ethos and personal commitment to achieving outstanding customer performance.
Why Join Us?


  • Full training provided with career development opportunities.
  • Be part of a great, friendly, diverse, and multilingual team.
  • Enjoy numerous perks and benefits.


If you believe you have the skills and experience relevant for this position, please upload your CV and a cover letter (in one document).

To apply or find out more please contact or

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