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.

Role Summary

The Data Infrastructure team at Mistral AI is architecting the backbone of our frontier model training and fine-tuning ecosystem. We are building the specialized compute and data fabrics required to power the development of world-class AI. Our vision is to operate some of the largest compute fleets in production and build data lakes and metadata systems with a roadmap toward exabyte-scale architecture. We are currently building a high-performance training platform designed for massive scale across both on-premise and cloud-native Kubernetes environments. We are leading a strategic transition from legacy scheduling to modern orchestration, implementing sophisticated multi-cluster orchestration and cloud-bursting capabilities to better utilize our global resources and ensure our researchers have seamless access to compute wherever it resides. Our mission is to evolve our current systems into a durable yet flexible platform.

Location: Paris / Warsaw / Zurich / London (hybrid) or remote EU/UK with one hub visit per month.

About 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.

In this role, you will:

• Build & Scale: Reach the 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: Lead the 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 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.

You might thrive in this role if 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.

Location & Remote

This role is primarily based at one of our European offices (Paris, London, Warsaw, and Zurich). We will prioritize candidates who either reside there or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. In certain specific situations, we will also consider remote candidates based in one of the countries listed in this job posting-currently France, UK, Poland, and Switzerland. In that case, we ask all new hires to visit the local hub: for the first week of their onboarding (accommodation and travelling covered) and then at least 3 days per month.

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.

• 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.

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. #J-18808-Ljbffr

The Data Infrastructure team at Mistral AI is architecting the backbone of our frontier model training and fine-tuning ecosystem. We are building the specialized compute and data fabrics required to power the development of world-class AI. Our vision is to operate some of the largest compute fleets in production and build data lakes and metadata systems with a roadmap toward exabyte-scale architecture. We are currently building a high-performance training platform designed for massive scale across both on-premise and cloud-native Kubernetes environments. We are leading a strategic transition from legacy scheduling to modern orchestration, implementing sophisticated multi-cluster orchestration and cloud-bursting capabilities to better utilize our global resources and ensure our researchers have seamless access to compute wherever it resides. Our mission is to evolve our current systems into a durable yet flexible platform.