Research Engineer, Mistral AI
Data Infrastructure
Generative AI model developers
Open for applications
Generative AI model developers
501-1000 employees
Open for applications
501-1000 employees
Company mission
To make frontier AI ubiquitous, and to provide tailor-made AI to all the builders.
Role
Who you are
- 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 the job involves
- 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
Our take
Founded by Facebook AI researchers, Mistral AI focuses on developing open-source generative AI models to "make AI useful." It emerged in early 2023, quickly achieving a $260 million valuation.
Mistral features up to 176 billion parameters, and its open-source nature has sparked concerns about potential misuse. However, Mistral remains a formidable competitor in the AI landscape, challenging models from Google and Meta.
In 2025, Mistral secured a massive €1.7 billion funding round, raising its valuation to €11.7 billion. This Series B funding, led by European chip firm ASML, underscores significant interest in alternatives to ChatGPT and a push away from Silicon Valley dependence by European AI competitors.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 5 rounds)
Sep 2025
$1.9bn
SERIES C
Jun 2024
$523.6m
SERIES B
Total funding: $3.0bn
Company benefits
- Competitive bonus structure
- Equity
- Opportunities for professional growth and development
Company HQ
Villette, Paris, France
Leadership
Timothee Lacroix
(Co-Founder & CTO)Previously PhD and Software Engineer Intern at Facebook and Visiting Undergraduate at CAlab UCSD
Guillaume Lample
(Co-Founder & Chief Scientist)Research Student and Scientist at Facebook AI and Research Intern at Jane Street Capital
Arthur Mensch
(Co-Founder & CEO)Previously Staff Research Scientist at DeepMind, Post-doc researcher at École normale supérieure, Visiting Researcher at NYU Courant Institute of Mathematical Sciences and PhD Student at Inria
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