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Mistral AI

Open-weight LLMs and enterprise AI deployment

Applied Scientist - Formal Methods

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Fluency in English and the ability to explain complex technical concepts to technical and non-technical audiences.
  • 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.
  • Ability to work independently and navigate uncertainty.
  • A track record of success through personal projects, professional projects, or academia.

Responsibilities

  • Design, train, and deploy state-of-the-art large language models and apply them to diverse use cases.
  • Run pre-training and post-training, and deploy state-of-the-art models on large clusters.
  • Generate and curate datasets for theorem proving and software verification, and build evaluators and benchmarks for formal reasoning.
  • Develop tools and frameworks to facilitate data generation, model training, evaluation, and deployment.
  • Collaborate with internal and external science, engineering, and product teams to deliver high-impact AI solutions and tackle complex use cases.
  • Manage research projects and communications with client research teams.

Desired Qualifications

  • A PhD or Master's degree in a relevant field, such as Computer Science, Mathematics, or Machine Learning.
  • Experience with autoformalization, proof automation, or verified code generation.
  • Experience with reinforcement learning using verifiable rewards, ideally with Lean or other proof assistants.
  • Contributions to a large open-source or industry codebase.
  • Publications in top academic journals or conferences.
  • Interest in improving existing code through typing, tests, and 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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