Multilingual Model Behavior Architect

Multilingual Model Behavior Architect

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Define and measure model behaviour across languages, ensuring cultural alignment and naturalness.
  • Company: Join Mistral, a leader in multilingual AI innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and diversity.
  • Why this job: Shape the future of multilingual models and make a global impact.
  • Qualifications: Experience in AI, linguistics, or related fields with a passion for language.

The predicted salary is between 60000 - 80000 Β£ per year.

Mistral is seeking a Model Behavior Architect for the Multilingual team to define and measure how our models behave across languages. You will set standards for language adherence, naturalness, and cultural alignment to ensure consistent performance globally.

You will collaborate with the Science team to implement evaluations, data guidelines, and synthetic testing environments for multilingual settings, shaping how models reflect linguistic nuances and regional culture.

Multilingual Model Behavior Architect employer: mistral

Mistral is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from competitive salaries, equity options, comprehensive health insurance, and visa sponsorship, alongside ample opportunities for professional growth within the rapidly evolving field of AI. Joining Mistral means being part of a forward-thinking team dedicated to making a meaningful impact through strategic partnerships with leading publishers and academic institutions.

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Contact Details:

mistral Recruitment Team

We think you need these skills to ace Multilingual Model Behavior Architect

Language Adherence Standards
Naturalness Measurement
Cultural Alignment
Collaboration with Science Team
Evaluation Implementation
Data Guidelines Development
Synthetic Testing Environments