Data Infrastructure Engineer — Remote EU AI Compute

Lindus Health; Warszawa; Hybrid; PLN 390,000 - 607,000; Full time

Benefits offered by this job

Healthcare coverage

Retirement plans

Relocation support

Wellness programs

Meal allowance

Transportation allowance

Job summary

Mistral AI is building the next generation of data infrastructure for massive AI workloads, spanning on-premise and cloud-native Kubernetes environments. You will contribute to scaling compute fleets, storage systems, and end-to-end data pipelines for high-performance model training and fine-tuning.

The role emphasizes decoupled control/data planes, production-grade pipelines, and on-call rotations to support critical training jobs across multiple regions.

Qualifications

• 4+ years in Data Infrastructure, MLOps, or Infrastructure Engineering.
• Experience with large-scale compute and storage platforms.
• Proficiency in Python.
• Experience debugging multi-cluster distributed systems.
• Comfort with ambiguity in a rapid-growth AI environment.

Responsibilities

• Build & Scale: operate massive distributed compute and storage systems.
• Global Orchestration: multi-cluster orchestration across regions.
• Design Future-Proof Storage: transition to modern storage formats.
• Platform Engineering: develop internal training platform on Kubernetes/SLURM.
• Metadata & Lineage: ensure visibility and data/model lineage.
• Operational Excellence: scalable, reliable cloud-native deployments.

Skills

Python

Kubernetes

Distributed systems

MLOps

Data infrastructure

Tools

Kubernetes tooling

SLURM

Job description

Mistral AI is building the next generation of data infrastructure for massive AI workloads, spanning on-premise and cloud-native Kubernetes environments. You will contribute to scaling compute fleets, storage systems, and end-to-end data pipelines for high-performance model training and fine-tuning.

The role emphasizes decoupled control/data planes, production-grade pipelines, and on-call rotations to support critical training jobs across multiple regions.