Mistral AI에서 Site Reliability Engineer를 채용합니다. 7년 이상의 SRE/DevOps 경력과 Kubernetes, Terraform, 클라우드 인프라 운영 능력이 필수입니다. AI 모델 학습 및 서비스 환경의 안정성과 확장성을 책임지며, 연구팀과 협업하여 인프라 자동화와 고가용성 시스템을 구축합니다. 유럽 전역에서 원격 근무가 가능하며, AI 기술의 미래를 함께 만들어갈 분을 찾습니다.
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 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
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
• 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
• 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
• 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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