Site Reliability Engineer

About the role

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

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