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Open-Source AI · Paris
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.
We’re looking for passionate and talented Software Engineers to join our Compute team. In this role, you’ll have the opportunity to shape and deliver on-demand Kubernetes clusters with GPU support for Training, Inference, and general-purpose CPU workloads.
More information on Mistral Compute here: https://mistral.ai/products/compute
We will prioritize candidates who either reside in one of our main offices (Paris, London, NYC) or are open to relocating. We will also consider remote candidates based in the following countries:
EMEA: France, United Kingdom, Germany, Switzerland, Netherlands, Spain, Austria, Poland, Luxembourg
Americas: USA, Canada
We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. In any case, we ask all new hires to visit our Paris HQ office (accommodation and travelling covered)
• for the first week of their onboarding
• then at least 3 days every month
Software Development: Design, build, and maintain scalable control plane services, operators, and custom controllers for Kubernetes
Cluster lifecycle management: Develop automation including provisioning, upgrades, patching, and decommissioning.
Monitoring and Observability: Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
Internal tooling: Create workflows, tools, APIs, and command-line interfaces (CLIs) to empower customers and ML/AI teams to deploy and monitor inference services efficiently.
Reliability: Design resilient systems capable of gracefully handling failures in large-scale distributed environments.
Investigation: identify and resolve unique cluster issues at a low level, documenting findings for future reference.
Incident Response: Participate in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences
Master’s degree in Computer Science, Engineering or a related field
5+ years of experience in a similar role (Software Engineer, DevOps, SRE ...)
Strong coding proficiency (ideally Golang) and knowledge of software development best practices
Mastery of containerization and orchestration tools (Docker, Kubernetes...)
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)
Strong problem-solving abilities and attention to detail.
Ability to own and deliver end-to-end features with minimal oversight.
Excellent communication skills and collaborative attitude.
Team-oriented, humble and eager to learn.
Strong understanding of networking, security, and system administration concepts
Now, it would be ideal if you had experience with:
high-performance computing (HPC) systems and workload managers (Slurm)
monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack...)
networking, storage, security, and system administration concepts
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page.
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.