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求人Mistral AI

Site Reliability Engineer

Mistral AI

Site Reliability Engineer

Mistral AI

Paris

·

On-site

·

Full-time

·

1mo ago

福利厚生

Healthcare

Parental Leave

必須スキル

DevOps

SRE

Kubernetes

Docker

Terraform

Python

Go

Bash

Prometheus

Grafana

About Mistral

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.

Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.

Role Summary:

We are seeking highly experienced Site Reliability Engineers (SRE) to shape the reliability, scalability and performance of our platform and customer facing applications. You will work closely with our software engineers and research teams to ensure our systems meet and exceed our internal and external customers' expectations.

  • Location: Remote
  • Europe
    Reporting line: Team Lead, Site Reliability Engineer

What you will do

As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.

  • Operations (50%)

  • Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads

  • Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters

  • Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)

  • Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime

  • Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs

  • Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences

  • Development (50%)

  • Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform

  • Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments

  • Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure

  • Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)

  • Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements

  • Document processes and procedures to ensure consistency and knowledge sharing across the team

  • Contribute to open-source projects, research publications, blog articles and conferences

About you

  • Master’s degree in Computer Science, Engineering or a related field
  • 7+ years of experience in a DevOps/SRE role
  • Strong experience with cloud computing and highly available distributed systems
  • Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)
  • Experience working against reliability KPIs (observability, alerting, SLAs)
  • Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)
  • Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)
  • Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
  • Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices
  • Strong understanding of networking, security, and system administration concepts
  • Excellent problem-solving and communication skills
  • Self-motivated and able to work well in a fast-paced startup environment

Your application will be all the more interesting if you also have:

  • experience in an AI/ML environment
  • experience of high-performance computing (HPC) systems and workload managers (Slurm)
  • worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...)

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Mistral AIについて

Mistral AI

Mistral AI

Series B

Mistral AI is a French artificial intelligence company that develops and provides large language models and AI solutions. The company focuses on creating efficient and powerful AI models for various applications.

51-200

従業員数

Paris

本社所在地

$6.0B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

2.5

報酬

4.0

企業文化

4.2

キャリア

3.5

経営陣

2.3

72%

友人に勧める

良い点

Supportive team environment

Good compensation and benefits

Innovative projects and cutting-edge technology

改善点

Poor management and lack of direction

Work-life balance issues and heavy workload

Fast-paced stressful environment

給与レンジ

37件のデータ

Senior/L5

Senior/L5 · Solution Architect

1件のレポート

$273,000

年収総額

基本給

$210,000

ストック

-

ボーナス

-

$273,000

$273,000

面接体験

1件の面接

難易度

3.0

/ 5

期間

21-35週間

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Interview

4

Research Presentation

5

Team Matching

6

Offer

よくある質問

Machine Learning/AI Algorithms

Research Experience

Technical Knowledge

Coding/Implementation

Behavioral/STAR