About the role
About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users. 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 France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . Mistral AI participates in the E-Verify program By applying, you agree to our Applicant Privacy Policy . Role Summary We're hiring a Research Ops Manager to build and operate the shared systems that let Mistral's science organization move fast at scale. This role sits at the platform layer of Science Ops - the compute, data, access, vendor, and tooling systems that serve every research team. You'll own the operational layer underneath the research: designing clean systems, automating what should be automated, and making sure researchers spend their time on science, not infrastructure overhead. The ideal candidate is someone who is genuinely excited by problems at scale . You see a manual process and you think about how to automate it. You're fluent with modern coding tools - you vibe-code your own dashboards, scripts, and integrations to multiply your own leverage. You enjoy the operational puzzle of making complex systems feel simple to the people using them. What will you do Systems for Scale: Build and operate the shared infrastructure that lets research run smoothly - resource systems, data systems, tooling, observability. Design the operational layer that lets science scale without drag. Automation & Tooling: Use modern coding tools to build the internal automations that make Science Ops itself leverage-able - dashboards, integrations, self-service tooling, alerts. You'll be expected to build rather than just specify. Hiring & Onboarding Operations: Own the operational side of growing the science organization - interview logistics, leveling consistency, onboarding experience. Make sure every new hire is productive on day one, not day sixty. Cross-Functional Systems Partner: Partner with Finance, Legal, Security, and Engineering on the systems where science intersects with the rest of the company. Keep these interfaces clean and scale them as the organization grows. Strategic Communication: Translate
