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Mistral AI

Open-weight LLMs and enterprise AI deployment

Applied AI Engineer

AI Application EngineeringPosted on Nov 10
Full-timeSydney NSW, AustraliaNo salary listedIn-person

About the Job

Requirements

  • Fluency in English.
  • Experience as a technical individual contributor, such as a data scientist or software engineer, on AI-based products.
  • A proven track record implementing AI or machine learning products with application programming interfaces, back-end, and front-end interfaces.
  • Hands-on experience with fine-tuning large language models, advanced retrieval-augmented generation, or agentic use cases.
  • Deep understanding of machine learning and large language model concepts and algorithms.
  • Strong technical coding skills in Python.
  • Ability to explain complex technical concepts clearly to technical and non-technical audiences.
  • Contributions to open-source projects, particularly in the large language model space.

Responsibilities

  • Deploy production-ready AI use cases with significant business impact across diverse industries.
  • Develop generative AI applications, from consumer products to industrial solutions, driving technological transformation for customers.
  • Collaborate with researchers, AI engineers, and product teams on complex customer projects involving fine-tuning, advanced large language model applications, and contributions to open-source codebases.
  • Participate in pre-sales calls to understand client needs, challenges, and aspirations, providing technical guidance on Mistral’s products.
  • Work with product and science teams to continuously improve model and product capabilities based on customer feedback.

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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