Mistral AI에서 클라우드 플랫폼의 안정성과 확장성을 책임질 시니어 SRE를 채용합니다. 5년 이상의 SRE/DevOps 경력과 Kubernetes, 인프라 자동화 역량이 필수입니다. 베어메탈 환경 및 분산 시스템 운영 경험을 우대하며, AI 모델 학습을 위한 고성능 인프라 구축에 기여하게 됩니다. 글로벌 팀과 협업하며 AI 기술의 미래를 함께 만들어갈 분들의 많은 지원 바랍니다.
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.
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.
More information on Mistral Cloud here: https://mistral.ai/products/compute
• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures
• 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 customer-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
• Drive continuous improvement in infrastructure automation, deployment, and orchestration
• Collaborate with software engineers to develop and implement solutions that enable safe and reproducible model-training experiments
• Help build a cloud platform offering an abstraction layer between science, engineering and infrastructure
• 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.)
• 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
• Master’s degree in Computer Science, Engineering or a related field
• 5+ years of experience in a DevOps/SRE role
• Strong experience with bare metal infrastructure 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...)
• 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
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
Our first Engineering blog post is live, you can check it out here !
