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Jobs / Mistral.ai

Site Reliability Engineer

Mistral.ai · Parissenior

In short

  • ▸Ingeniero SRE que construye y mantiene infraestructura escalable para plataformas de IA.
  • ▸Trabaja con equipos de ML y software para garantizar alta disponibilidad y automatización en entornos HPC.
  • ▸Destaca por crear una plataforma independiente de nube que abstrae complejidades para equipos científicos.

Experiencia en entornos de IA/ML o computación de alto rendimiento (HPC)

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What they ask for

  • ✓Master en Ciencias de la Computación, Ingeniería o campo relacionado.
  • ✓7+ años en roles de SRE o DevOps con experiencia en sistemas distribuidos.
  • ✓Experiencia comprobada en resolución de incidencias en producción y rotaciones de on-call.
  • ✓Habilidades sólidas en CI/CD, contenedores (Docker), orquestación (Kubernetes).
  • ✓Conocimiento en herramientas de observabilidad: Prometheus, Grafana, ELK Stack o Datadog.
  • ✓Experiencia con infraestructura como código (Terraform o CloudFormation).

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About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector—co-creating customized AI systems that they can run on their terms. 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 Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role As a Site Reliability Engineer (SRE) on the Platform team, you will shape the reliability, scalability, and performance of our platform and customer-facing applications. You’ll work closely with software engineers and research teams to ensure our systems meet and exceed the expectations of both internal and external customers. This role balances day-to-day operations on production systems with long-term software engineering improvements. Your work will reduce operational toil, foster reliability, and ensure high availability for our web services, inference environments, and ML workloads. You’ll enable seamless replication of work environments across multiple HPC clusters, directly impacting the stability and efficiency of our AI platform. What You Will Do Design, build, and maintain scalable, highly available, and fault-tolerant infrastructures to support web services and ML workloads. Ensure our platform, inference, and model training environments are always highly available and enable seamless replication across HPC clusters. Operate systems and troubleshoot issues in production, including interrupts, on-call responses, and infrastructure scaling. Implement and improve monitoring, alerting, and incident response systems to minimize downtime and optimize performance. Develop and maintain workflows and tools for CI/CD, containerization, orchestration, monitoring, and logging. Participate in on-call rotations to respond to incidents and perform root cause analysis. Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, and Terraform. Collaborate with AI/ML researchers to enable safe and reproducible model-training experiments. Build a cloud-agnostic platform that abstracts infrastructure complexities for science and engineering teams. Design and develop new workflows, tooling, and automation to improve system reliability, availability, and performance. Work with the security team to ensure infrastructure adheres to best practices and compliance requirements. Document processes and procedures to ensure consistency and knowledge sharing across the team. What We're Looking For A Master’s degree in Computer Science, Engineering, or a related field. 7+ years of experience in a DevOps or SRE role, with strong expertise in cloud computing and distributed systems. Hands-on experience with site reliability issues, including root cause analysis, in-production troubleshooting, and on-call rotations. Proficiency in working with reliability KPIs, such as observability, alerting, and SLAs. Experience with CI/CD, containerization, and orchestration tools like Docker and Kubernetes. Knowledge of monitoring, logging, alerting, and observability tools such as Prometheus, Grafana, ELK Stack, or Datadog. Familiarity with infrastructure-as-code tools like Terraform or CloudFormation. Proficiency in scripting languages (Python, Go, Bash) and a strong understanding of software development best practices. Solid grasp of networking, security, and system administration concepts. Excellent problem-solving and communication skills, with the ability to work effectively in a collaborative environment.

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