Data Annotation Quality Specialist

À propos du poste

About Mistral

At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.

We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia. We are creative, low-ego and team-spirited.

At Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.

Mistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI.

Role Summary

We’re seeking highly motivated Data Quality Specialists with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. In this role, you will contribute to and audit human data annotations, upholding the highest standards of quality and efficiency.

Create high-quality data annotations, based on guidelines and continuous feedback, for the development and evaluation of AI models

In collaboration with the technical team, review/audit annotations in order to clarify requirements and share insights that improve annotation processes, tools, and guidelines Relevant academic background (science, technology, engineering, mathematics)

Professional proficiency in English, with strong writing and comprehension skills

Outstanding research and analytical skills

Exercises great judgement with complex instructions, limited data, and/or multiple information sources

Excellent communication, interpersonal, and organizational abilities

Adapts easily to dynamic environments and changing requirements

Appetite for operational work and high tolerance for repetitive tasks

Passionate about and committed to learning new tools and technologies PhD degree in science, technology, engineering, mathematics

Proven track record working with data

Fluency in multiple languages

Experience with code