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Mistral AI is seeking an Applied AI Engineer focused on ML infrastructure and DevOps to drive customer adoption of its frontier AI products and co-create customized solutions for enterprise clients in high-stakes industries including finance, manufacturing, defense, healthcare, and the public sector.
In this role, you will work directly with customers to understand their technical challenges and design end-to-end AI solutions. Your responsibilities span the full stack: from low-level GPU and infrastructure optimization through backend and frontend interfaces. You'll own customer onboarding, provide deployment and integration guidance, and ensure production-ready setups across cloud and on-premises environments.
Key responsibilities include:
- Onboarding customers on Mistral products and ensuring optimal production deployments
- Deploying state-of-the-art AI applications from consumer products to industrial use cases
- Collaborating with researchers, AI engineers, and product teams on complex customer projects involving deployment, scaling, and open-source contributions
- Participating in pre-sales technical discussions to understand client needs and provide guidance on Mistral technologies
- Explaining complex AI concepts to both technical and non-technical stakeholders
Required qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 2+ years of DevOps or Site Reliability Engineering experience
- Production experience deploying and managing AI-based systems
- Proficiency in Python
- Hands-on experience with Docker, Kubernetes, and containerization
- Strong knowledge of CI/CD pipelines and automated deployment tools
- Deep understanding of AWS, Azure, GCP, and on-premises infrastructure
- Experience with Infrastructure as Code tools (Terraform, Ansible)
- Excellent communication skills for technical and non-technical audiences
- Fluent in English
Ideal candidates may also have experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager; familiarity with PyTorch or TensorFlow; and open-source contributions in DevOps or AI.
