Mistral· Engineering & Infra· New York, NY
Site Reliability Engineer - NYC
Classified Tasks (15)
Automate 0%Augment 73%Human-Only 27%
Augment (11)
AI assists, human decides
Balance day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and improve reliability, availability, and performance
operational
Design scalable, highly available, and fault-tolerant infrastructure to support web services and ML workloads
technical
Ensure high availability of platform, inference, and model-training environments and enable seamless replication of work environments across multiple HPC clusters
operational
Implement and improve monitoring, alerting, and incident response systems to optimize system performance and minimize downtime
technical
Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging, alerting) for client-facing APIs and large training runs
technical
Drive continuous improvement of infrastructure automation, deployment, and orchestration using tools such as Kubernetes, Flux, and Terraform
technical
Collaborate with AI/ML researchers to develop and implement solutions enabling safe and reproducible model-training experiments
technical
Build a cloud-agnostic platform that provides an abstraction layer between scientific workflows and infrastructure
technical
Design and develop workflows and tooling (automation scripts, refactoring, API features, web apps, dashboards) to improve system reliability, availability, and performance
technical
Document processes and procedures to ensure consistency and knowledge sharing across the team
administrative
Contribute to open-source projects, research publications, blog articles, and conferences
creative
Human-Only (4)
Requires human judgment
Operate production systems and troubleshoot issues including interrupts, on-call responses, user administration, data extraction, and infrastructure scaling
operational
Participate in on-call rotations to respond to incidents and perform root cause analysis to prevent recurrence
operational
Collaborate with the security team to ensure infrastructure complies with security best practices and compliance requirements
communication
Work closely with software engineers and research teams to ensure systems meet internal and external customer expectations
communication
Job description
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. 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 • 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 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 a