Mistral· Research· Palo Alto
Research Engineer, Data Infrastructure
Classified Tasks (13)
Automate 0%Augment 92%Human-Only 8%
Augment (12)
AI assists, human decides
Build and operate next-generation data infrastructure including massive distributed compute fleets and storage systems
technical
Design and scale compute fleets and storage systems for high performance and scalability
technical
Architect and implement decoupled control and data planes
technical
Scale big-data compute and storage platforms to meet growing workload demands
technical
Implement secure and governed data access controls for MLOps and research workloads
technical
Architect and maintain multi-cluster orchestration layers to optimize workload placement across diverse hardware and regions
technical
Architect the transition to modern, columnar storage formats to handle fine-tuning datasets at exabyte scale
technical
Develop and contribute to the internal training platform to enable seamless model training and fine-tuning across Kubernetes and SLURM environments
technical
Implement and manage metadata and lineage systems to provide clear visibility across data and model pipelines
technical
Implement modern deployment workflows and CI/CD pipelines to manage cloud-native deployments and scale the data platform
technical
Architect migration away from legacy orchestrators to modern orchestration solutions
technical
Implement production-grade data and model pipelines from development through production
technical
Human-Only (1)
Requires human judgment
Participate in on-call rotations and respond to incidents affecting critical training jobs
operational
Job description
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. Role Summary 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 will you 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 o About you • 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.