Mistral

1 week ago

Research Engineer, Data Infrastructure

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Reposted: first listed 1 week ago

Job Summary

Build and operate Mistral’s next-generation data infrastructure, scaling massive compute fleets and storage systems for high performance. Help transition from legacy orchestration to decoupled control and data planes, architect multi-cluster orchestration, and design future-proof storage for fine-tuning at extreme scale. Contribute to an internal training platform across Kubernetes and SLURM, implement metadata/lineage systems, and support cloud-native deployments with reliable operations and on-call rotations.

Location: Palo Alto, San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Build and scale massive distributed compute and storage systems for high performance and scalability.
•Architect and maintain multi-cluster orchestration layers to optimize workload placement across hardware and regions.
•Design future-proof storage formats to support fine-tuning datasets at very large scale.
•Develop and improve an internal training platform enabling model training and fine-tuning across Kubernetes and SLURM environments.
•Implement metadata and lineage systems and support production-grade pipelines with cloud-native deployment workflows, including on-call rotations.

Key Requirements

•4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering.
•Experience or strong interest supporting foundational compute and storage platforms.
•Proficiency in Python and interest in solving the “brittle data lake” problem with modern, columnar storage standards.
•Experience with Kubernetes-native tooling and debugging large-scale distributed systems across multi-cluster environments.
•Comfort building and operating scalable, reliable, and secure systems in a rapid-growth AI environment.

Experience:4+ years

Skills:Problem-solvingDebuggingBuilding scalable systemsOperational excellenceComfort with ambiguity

Tech Stack:PythonKubernetesSLURMCloud-nativeDistributed systemsMulti-cluster orchestrationData lakeColumnar storage

Company Brief

Mistral

Develops state-of-the-art large language models and AI systems, offering models and developer tools for natural language understanding, generation, and enterprise AI integrations. Focuses on open research and production-ready model deployments.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Seed

Headquarters: Paris, France

Founded: 2023

Website LinkedIn

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Mistral

1 week ago

Research Engineer, Data Infrastructure

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Reposted: first listed 1 week ago

Job Summary

Location: Palo Alto, San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Build and scale massive distributed compute and storage systems for high performance and scalability.
•Architect and maintain multi-cluster orchestration layers to optimize workload placement across hardware and regions.
•Design future-proof storage formats to support fine-tuning datasets at very large scale.
•Develop and improve an internal training platform enabling model training and fine-tuning across Kubernetes and SLURM environments.
•Implement metadata and lineage systems and support production-grade pipelines with cloud-native deployment workflows, including on-call rotations.

Key Requirements

•4+ years of experience in Data Infrastructure, MLOps, or Infrastructure Engineering.
•Experience or strong interest supporting foundational compute and storage platforms.
•Proficiency in Python and interest in solving the “brittle data lake” problem with modern, columnar storage standards.
•Experience with Kubernetes-native tooling and debugging large-scale distributed systems across multi-cluster environments.
•Comfort building and operating scalable, reliable, and secure systems in a rapid-growth AI environment.

Experience:4+ years

Skills:Problem-solvingDebuggingBuilding scalable systemsOperational excellenceComfort with ambiguity

Tech Stack:PythonKubernetesSLURMCloud-nativeDistributed systemsMulti-cluster orchestrationData lakeColumnar storage

Company Brief

Mistral

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Seed

Headquarters: Paris, France

Founded: 2023

Website LinkedIn