Mistral AI
Site Reliability Engineer - Palo Alto
Mistral AI, San Francisco, California, United States, 94199
About Mistral
At Mistral AI, we are a tight-knit, nimble team dedicated to bringing our cutting-edge AI technology to the world. Our mission is to make AI ubiquitous and open. We are creative, low-ego, team-spirited, and have been passionate about AI for years. We hire people who thrive in competitive environments, because they find them more fun to work in. We hire passionate women and men from all over the world. Our teams are distributed between France, UK and USA.
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 customers' expectations.
Key Responsibilities
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. Ensure 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 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. Qualifications & Profile Master’s degree in Computer Science, Engineering or a related field. 5+ 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...). What We Offer Ability to shape the exciting journey of AI and be part of the very early days of one of Europe’s hottest startups. A fun, young, multicultural team and collaborative work environment — based in Paris, London and San Francisco. Competitive salary and bonus structure. Comprehensive benefits package. Opportunities for professional growth and development.
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(50%) Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads. Ensure 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 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. Qualifications & Profile Master’s degree in Computer Science, Engineering or a related field. 5+ 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...). What We Offer Ability to shape the exciting journey of AI and be part of the very early days of one of Europe’s hottest startups. A fun, young, multicultural team and collaborative work environment — based in Paris, London and San Francisco. Competitive salary and bonus structure. Comprehensive benefits package. Opportunities for professional growth and development.
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