Research Engineer, Data Infrastructure

Mistral AI

$120K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years in Data Infrastructure, MLOps, or Infrastructure Engineering
  • Experience or strong interest in foundational compute and storage platforms
  • Proficient in Python, addressing modern storage challenges
  • Familiar with Kubernetes-native tooling and debugging distributed systems
  • Ability to build scalable, reliable, and secure systems
  • Comfortable with ambiguity in a rapid-growth AI setting

Responsibilities

  • Build and scale distributed compute and storage systems
  • Architect and maintain multi-cluster orchestration for workload optimization
  • Design transition to modern storage formats for massive datasets
  • Contribute to internal training platform for seamless model training
  • Implement systems for data visibility and lineage management
  • Manage cloud-native deployments for reliability and efficiency

Benefits

  • Comprehensive healthcare coverage
  • Parental leave options
  • Retirement plans
  • Relocation support available
  • Wellness programs to support well-being
  • Meal and transportation allowances
  • Location-specific perks
Full Job Description
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.

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