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Mistral AI

Open-weight LLMs and enterprise AI deployment

Site Reliability Engineer - Platform

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeÎle-de-France, FranceNo salary listedIn-person

About the Job

Requirements

  • A Master’s degree in Computer Science, Engineering, or a related field.
  • At least 7 years of experience in a DevOps or Site Reliability Engineering role, with strong expertise in cloud computing and distributed systems.
  • Hands-on experience with site reliability issues, including root cause analysis, in-production troubleshooting, and on-call rotations.
  • Proficiency with reliability KPIs, observability, alerting, and service-level agreements.
  • Experience with continuous integration and continuous delivery, containerization, and orchestration tools such as Docker and Kubernetes.
  • Knowledge of monitoring, logging, alerting, and observability tools such as Prometheus, Grafana, ELK Stack, or Datadog.
  • Familiarity with infrastructure-as-code tools such as Terraform or CloudFormation.
  • Proficiency in Python, Go, and Bash, with a strong understanding of software development best practices.
  • A solid understanding of networking, security, and system administration concepts.
  • The ability to work effectively in a collaborative environment.

Responsibilities

  • Design, build, and maintain scalable, highly available, and fault-tolerant infrastructures supporting web services and machine-learning workloads.
  • Ensure platform, inference, and model-training environments remain highly available and support seamless replication across high-performance computing clusters.
  • Operate systems and troubleshoot production issues, including interrupts, on-call responses, and infrastructure scaling.
  • Implement and improve monitoring, alerting, and incident-response systems to minimize downtime and optimize performance.
  • Develop and maintain workflows and tools for continuous integration and continuous delivery, containerization, orchestration, monitoring, and logging.
  • Participate in on-call rotations, respond to incidents, and perform root-cause analysis.
  • Drive continuous improvement in infrastructure automation, deployment, and orchestration using Kubernetes, Flux, and Terraform.
  • Collaborate with artificial-intelligence and machine-learning researchers to enable safe and reproducible model-training experiments.
  • Build a cloud-agnostic platform that abstracts infrastructure complexities for science and engineering teams.
  • Design and develop workflows, tooling, and automation to improve system reliability, availability, and performance.
  • Work with the security team to ensure infrastructure adheres to best practices and compliance requirements.
  • Document processes and procedures to ensure consistency and knowledge sharing across the team.

Desired Qualifications

  • Experience in an artificial-intelligence or machine-learning environment, high-performance computing systems, or modern AI-oriented solutions such as Fluidstack, CoreWeave, or Vast.

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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