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Mistral AI

Open-weight LLMs and enterprise AI deployment

Research Software Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A Master’s degree in Computer Science or equivalent experience.
  • At least 4 years of experience building and operating large-scale or distributed systems.
  • Strong software-design instincts, including modular code, tests, continuous integration and continuous delivery, and observability.
  • Fluency in Python and one systems language: C++, Rust, Go, or Java.
  • Hands-on experience with container orchestration and schedulers such as Kubernetes, K8s, or SLURM.
  • Ability to profile performance, optimize input/output, and automate workflows.

Responsibilities

  • Accelerate researchers by owning complex parts of large-scale pipelines and delivering robust internal tooling.
  • Connect research with product by exposing clean application programming interfaces, automating model pushes, and surfacing live metrics.
  • Write efficient, well-tested Python and systems code; enforce code review, continuous integration, and observability.
  • Design and optimize distributed services using Kubernetes or SLURM for jobs involving thousands of graphics processing units.
  • Prototype utilities such as command-line interfaces and dashboards, and develop them into stable, shared libraries.

Desired Qualifications

  • Exposure to machine learning workloads or data-processing pipelines.
  • Experience with graphics processing unit clusters or CUDA.
  • Open-source contributions or widely used internal tools.

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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