招聘
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 Cloud platform and customer facing applications. You will work closely with our software engineers and product teams to ensure our systems meet and exceed our internal and external customers' expectations.
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More information on Mistral Cloud here: https://mistral.ai/products/compute What you will do Operations
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Design, build, and maintain scalable, highly available and fault-tolerant infrastructures
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Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
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Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
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Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our customer-facing APIs and large training runs
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Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences
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Development
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Drive continuous improvement in infrastructure automation, deployment, and orchestration
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Collaborate with software engineers to develop and implement solutions that enable safe and reproducible model-training experiments
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Help build a cloud platform offering an abstraction layer between science, engineering and infrastructure
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Design and develop new workflows and tooling to improve the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)
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Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
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Document processes and procedures to ensure consistency and knowledge sharing across the team
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Contribute to open-source projects, research publications, blog articles and conferences
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About you
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Master’s degree in Computer Science, Engineering or a related field
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5+ years of experience in a DevOps/SRE role
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Strong experience with bare metal infrastructure and highly available distributed systems
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Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...)
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Experience working against reliability KPIs (observability, alerting, SLAs)
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Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...)
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Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...)
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Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
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Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices
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Strong understanding of networking, security, and system administration concepts
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Excellent problem-solving and communication skills
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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...)
- Hiring Process
- Introduction Call - 30 min
- Manager Interview - 30 min
- Technical Interview / System Design - 45 min
- Technical Interview / Deep Dive - 60 min
- Culture-fit Discussion - 30 min
- References
Our Culture We're driven to build a strong company culture and are looking for individuals with solid alignment with the following: - Reason with rigor
- Are you audacious enough?
- Make our customers succeed
- Ship early and accelerate
- Leave your ego aside
Engineering blog Our first Engineering blog post is live, you can check it out here !
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关于Mistral AI

Mistral AI
Series BMistral 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
员工数
Paris
总部位置
$6.0B
企业估值
评价
3.8
10条评价
工作生活平衡
2.5
薪酬
4.0
企业文化
4.2
职业发展
3.5
管理层
2.3
72%
推荐给朋友
优点
Supportive team environment
Good compensation and benefits
Innovative projects and cutting-edge technology
缺点
Poor management and lack of direction
Work-life balance issues and heavy workload
Fast-paced stressful environment
薪资范围
37个数据点
Senior/L5
Senior/L5 · Solution Architect
1份报告
$273,000
年薪总额
基本工资
$210,000
股票
-
奖金
-
$273,000
$273,000
面试经验
1次面试
难度
3.0
/ 5
时长
21-35周
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Research Presentation
5
Team Matching
6
Offer
常见问题
Machine Learning/AI Algorithms
Research Experience
Technical Knowledge
Coding/Implementation
Behavioral/STAR
新闻动态
Generative AI Platforms - Trend Hunter
Trend Hunter
News
·
5d ago
How France’s Mistral Built A $14 Billion AI Empire By Not Being American - Forbes
Forbes
News
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5d ago
Connect the dots: Build with built-in and custom MCPs in Studio - Mistral AI
Mistral AI
News
·
6d ago
The OpenAI / TBPN Audit: Why Anthropic’s Next Acquisition Should Be a Regulatory Network
https://preview.redd.it/q7ltkacfu2tg1.jpg?width=3000&format=pjpg&auto=webp&s=261ce6e7090baf84297a882ffa5b7e62f0d09955 # Forensic Audit: OpenAI’s TBPN Acquisition, the Enterprise Trust Gap, and the Dawn of Regulatory Media **Listen to audio at** [**https://enoumen.substack.com/p/the-openai-tbpn-audit-why-anthropics**](https://enoumen.substack.com/p/the-openai-tbpn-audit-why-anthropics) OpenAI just spent hundreds of millions to buy the Silicon Valley narrative. It’s a brilliant cons
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2w ago
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