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Mistral AI

Open-weight LLMs and enterprise AI deployment

AI Scientist

AI ResearchConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A track record of contributing to relevant scientific domains, such as publications or open-source projects.
  • Hands-on experience with AI frameworks such as PyTorch or JAX, or distributed systems such as Ray or Kubernetes.
  • Proficiency in at least one programming language, such as Python, Rust, Go, or Java.
  • Ability to design complex software systems and transition them into production environments.
  • Experience with training large transformer models in a distributed setting.
  • Familiarity with the full machine learning operations stack, including fine-tuning, evaluation, and deployment.
  • Strong engineering competence, with a focus on building scalable and reliable systems.

Responsibilities

  • Research and develop novel methods to advance the capabilities of large language models.
  • Design and implement tooling and infrastructure for training, evaluating, and analysing artificial intelligence models at scale.
  • Collaborate with scientists, engineers, and product teams to ship artificial intelligence systems with tangible impact.
  • Explore and innovate across use cases such as reasoning, code generation, and agent-based systems.
  • Work with multimodal data, including text, image, and speech, to expand model capabilities.
  • Optimise distributed systems to improve the efficiency and scalability of model training.
  • Contribute to the open-source community by releasing frontier models for public use.

Desired Qualifications

  • A self-starter mindset with the autonomy to drive projects forward and collaborate effectively in a team.

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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