Model Behaviour Architect- Multilingual

 

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

 

We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users.

 

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. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.

 

Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.

About the role

As a Model Behaviour Architect in the Multilingual team, you define and measure what good model behaviour looks like across languages, not just in English.

We are looking for people who have built a career in engineering, machine learning, and large language models and are experts in model evaluation, policy writing, and building eval pipelines for complex tasks. Your role is to work hand in hand with our Science team to define what “good” means for multilingual behaviour: language adherence, naturalness, cultural alignment, and consistent capability across the languages in which our models are deployed.

Join us if you are passionate about tackling cutting-edge, open-ended research challenges and transforming your insights into best-in-class models that work for users in every language and culture they belong to.

What you will do

• Interact with models across languages to identify where multilingual behaviour can be improved

• Gather internal and external feedback to scope areas for improvement

• Define what high-quality behavior means per language

• Design and implement evals, data guidelines, data generation, and synthetic testing environments for multilingual settings

• Shape how models reflect the cultural context of the users and regions they serve

• Identify and fix edge-case behaviors through rigorous cross-language testing

• Develop robust evaluation pipelines for model candidates

• Work collaboratively with AI Scientists