About the role
Research Engineer, Data Infrastructure 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 This role focuses on building and operating the next generation of data infrastructure at Mistral AI. You will be a core contributor to our evolution, helping us design and scale massive compute fleets and storage systems designed for high performance and scalability. You will help us move toward a future of decoupled control and data planes, scaling big data compute and storage platforms while ensuring secure and governed data access for MLOps and research. You will take full lifecycle ownership: from architecting the migration away from legacy orchestrators to implementing production-grade pipelines and participating in on-call rotations for critical training jobs. What You Will Do • Build & Scale: Help us reach our goal of operating massive distributed compute and storage systems • Global Orchestration: Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions. • Design Future-Proof Storage: Architect our transition to modern storage formats to handle fine-tuning datasets at a scale that anticipates exabyte growth. • Platform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine-tuning capabilities across Kubernetes and SLURM based environments. • Metadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity. • Operational Excellence: Use modern deployment workflows to manage cloud-native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient. What We're Looking For • Have 4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering. • Have experience or a strong interest in supporting foundational compute and storage platforms. • Are proficient in Python and enjoy solving the "brittle data lake" problem with modern, columnar storage standards. • Are well-versed in Kubernetes-native tooling and excited to debug large-scale distributed systems across multi-cluster environments. • Take pride in building and operating scalable, reliable, and secure systems from the ground up. • Are comfortable with ambiguity and the challenges of building high-scale infrastructure in a rapid-growth AI environment. What We Offer 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. Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy. Palo Alto
Key responsibilities
- check_circleCollaborate with the team on day-to-day project tasks
- check_circleLearn tools and processes used by the organization
- check_circleDocument work and participate in team meetings
- check_circleSupport quality checks and continuous improvement
Requirements
- check_circleBuild & Scale: Help us reach our goal of operating massive distributed compute and storage systems
- check_circleGlobal Orchestration: Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions.
- check_circleDesign Future-Proof Storage: Architect our transition to modern storage formats to handle fine-tuning datasets at a scale that anticipates exabyte growth.
- check_circlePlatform Engineering: Contribute to the development of our internal training platform, ensuring seamless model training and fine-tuning capabilities across Kubernetes and SLURM based environments.
- check_circleMetadata & Lineage: Implement and manage systems to provide clear visibility and lineage as our data and model pipelines grow in complexity.
- check_circleOperational Excellence: Use modern deployment workflows to manage cloud-native deployments, ensuring our data platform can scale by orders of magnitude while remaining reliable and efficient.
- check_circleHave 4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering.
- check_circleHave experience or a strong interest in supporting foundational compute and storage platforms.
- check_circleAre proficient in Python and enjoy solving the "brittle data lake" problem with modern, columnar storage standards.
- check_circleAre well-versed in Kubernetes-native tooling and excited to debug large-scale distributed systems across multi-cluster environments.
- check_circleTake pride in building and operating scalable, reliable, and secure systems from the ground up.
- check_circleAre comfortable with ambiguity and the challenges of building high-scale infrastructure in a rapid-growth AI environment.
Skills & keywords
Benefits & perks
- check_circleMentorship
- check_circleCertificate of completion
- check_circleFlexible work arrangement where applicable