Mistral AI에서 데이터 인프라를 설계하고 운영할 엔지니어를 찾습니다. 4년 이상의 경력과 Python, Kubernetes 활용 능력이 필수입니다. 대규모 분산 컴퓨팅 환경을 구축하고, 차세대 스토리지 아키텍처를 설계하며, 모델 학습 플랫폼의 안정성을 책임지는 핵심 역할을 수행하게 됩니다. 빠르게 성장하는 AI 환경에서 확장 가능한 시스템을 구축하는 데 열정적인 분을 환영합니다.
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.
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.
• 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.
• 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.
