M

Mistral AI

Open-weight LLMs and enterprise AI deployment

Applied Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • 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

  • 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, work on evaluations, and ensure model performance meets expectations.
  • Develop tools and frameworks for data generation, model training, evaluation, and deployment.
  • Collaborate with cross-functional teams to tackle complex use cases using agents and retrieval-augmented generation pipelines.
  • Manage research projects and communications with client research teams.

Desired Qualifications

  • Research experience in agents, multimodality, robotics, diffusion, or time series.
  • Contributions to a large codebase used by many, either open source or in industry.
  • A track record of publications in top academic journals or conferences.
  • Interest in improving existing code by fixing typing issues, adding tests, and improving continuous integration pipelines.
  • A PhD or master's degree in a relevant field such as Mathematics, Physics, Machine Learning, or Computer Science and Engineering; exceptional candidates from other backgrounds are also encouraged to apply.

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

Recently Posted Jobs

Explore more opportunities at Mistral AI

See more jobs