Mistral AI
AI Frontier · Open-weight LLMs
- HQ
- Paris, FR
- Founded
- 2023
- Size
- 200+
- Website
- mistral.ai
- Blog
- mistral.ai
Products
AI Frontier · Open-weight LLMs
Currently tracking 67 active AI roles, down 73% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Mistral AI currently has 83 active AI-related roles in our index. The most common open titles are: Research Engineer, Data Infrastructure (2), AI Deployment Strategist - Australia, AI Deployment Strategist - Luxembourg, AI Deployment Strategist - MENA, AI Deployment Strategist - Marseille. Most positions are in Engineering and Product.
Mistral AI's active AI hiring is concentrated in: agents (35%), application (29%), data (10%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Mistral AI is hiring AI talent in: France (52 roles), Singapore (7 roles), United States (6 roles), Germany (4 roles).
Job postings at Mistral AI most frequently reference: model serving, fine tuning, agent orchestration, rag, inference infra.
In the past 30 days, Mistral AI has posted 12 new AI-related roles. That is a -75% change versus the prior 30 days (48 → 12).
Mistral AI currently has 76 active AI-related job listings. The majority of these roles are focused on agents, making up 34% of the openings, followed by application-focused roles at 32%. Engineering is the most frequently listed function. The company is actively hiring, with 42 new AI roles posted in the last 30 days, representing a 27% increase compared to the previous 30-day period.
| Title | Stage | AI score |
|---|---|---|
| AI Scientist - Warsaw AI Scientist role at Mistral AI focusing on research and development of novel methods for large language models across various use cases and modalities. The role involves building tooling and infrastructure for training, evaluation, and analysis, and collaborating to ship AI systems with real-world impact. Requires strong software engineering skills, experience with AI frameworks or distributed systems, and high engineering competence for production readiness. Ideal candidates have experience training large transformer models, navigating the MLOps stack, and a strong publication record. | PretrainPost-train | 9 |