Platform Engineer, Mistral AI

• 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, working against reliability KPIs, participating in on-call rotations...)
• Hands-on experience with CI/CD, containerization and orchestration tools
• Knowledge of monitoring, logging, alerting and observability tools like Prometheus, Grafana, ELK Stack or Datadog
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Proficiency in scripting languages such as Python, Bash, or PowerShell 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

Desirable

• We are seeking highly experienced and motivated Platform Engineers to build scalable services and ensure a high-availability experience to empower our AI research team in their daily work
• As a ML Platform 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%)
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
• Make sure our model training environments are always highly available and enable seamless replication of work environments across several HPC clusters
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our large training runs and our client-facing APIs
• Participate occasionally in on-call rotations to resolve incidents occurring out-of-hours
• Engineering (50%)
• 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.)
• Ensure compliance with security best practices and industry standards
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles, conference attending