Offer summary

Qualifications:

Native-level proficiency in French is required., Strong attention to detail and language skills are essential., Experience with text annotation or linguistics is a plus., Ability to work independently and manage time effectively..

Key responsibilities:

Annotate and label French-language text according to project guidelines.

Identify and correct grammar, spelling, and syntax errors.

Evaluate the fluency and coherence of AI-generated content.

Provide structured feedback to enhance future model outputs.

At Your Personal AI, we are at the forefront of facilitating advanced AI and ML projects through our specialized data collection services. Our expertise spans a wide spectrum of data types – from intricate audio recordings, comprehensive image collections to detailed annotations and varied data formats. We pride ourselves on our ability to handle substantial and complex projects, ensuring precision and quality in every dataset we deliver. With a focus on global reach, particularly in Europe and North America, we leverage our extensive network and local insights to manage and execute projects across various regions. We understand the pivotal role of data in AI and ML advancements and are committed to being a trusted partner in your AI journey. Whether you are looking to enhance your AI models with comprehensive datasets or seeking tailored data solutions, Your Personal AI is your ideal partner. Connect with us to explore how we can empower your AI and ML projects with our specialized services.

Job description

Your Personal AI (YPAI) is building advanced multilingual AI systems for global use. We are currently recruiting skilled French Text Annotators to support projects that train large language models to better understand written French.

This freelance opportunity is ideal for native-level speakers who are precise, language-savvy, and comfortable working independently.

Position Overview

As a French Text Annotator, you will evaluate, tag, and correct AI-generated French text. The work involves applying specific labeling guidelines, improving clarity and accuracy, and helping identify linguistic patterns that improve model output.