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Mistral AI

Open-weight LLMs and enterprise AI deployment

Applied Scientist

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedIn-person

About the Job

Requirements

  • Fluency in English and Korean.
  • Expertise with PyTorch or JAX.
  • Ability to contribute independently to a large codebase with little guidance.
  • Ability to write clean, readable, high-performance, fault-tolerant Python code.
  • A track record of success through personal projects, professional projects, or academia.

Responsibilities

  • Develop state-of-the-art models across text, image, and speech modalities, applying novel methods and research ideas to use cases and domains.
  • Run pre-training and post-training and deploy state-of-the-art models on clusters with thousands of GPUs.
  • Generate and curate data for pre-training and post-training, and work on evaluations to ensure model performance.
  • Develop tools and frameworks for data generation, model training, evaluation, and deployment.
  • Collaborate with cross-functional teams on complex use cases using agents and retrieval-augmented generation pipelines.
  • Manage research projects and communications with client research teams.

Desired Qualifications

  • A PhD or master's degree in a relevant field, such as Mathematics, Physics, or Machine Learning.
  • A variety of research experience, such as agents, multimodality, robotics, diffusion, or time series.
  • Contributions to a large codebase used by many, in open source or industry.
  • A track record of publications in top academic journals or conferences.
  • Experience improving existing code by fixing typing issues, adding tests, and improving continuous integration pipelines.

About the Company

Mistral AI

Open-weight LLMs and enterprise AI deployment

Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.

Company size
1,001-5,000
Company stage
Series D
Total funding
$7.2B
Headquarters
Paris, France
Founded
2023

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