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Mistral is seeking an Applied AI Engineer to drive enterprise adoption of its full-stack AI solutions. The Applied AI team operates as customer-facing technical experts, working directly with enterprise clients from pre-sales through production deployment across high-stakes industries including finance, manufacturing, defense, healthcare, and the public sector.
In this role, you will own end-to-end project execution, deploying production AI use cases with significant business impact. You'll work on state-of-the-art generative AI applications spanning consumer products to industrial implementations, collaborating closely with customers to drive technological transformation. Your responsibilities include:
- Deploying production use cases across various industries with measurable business impact
- Developing and implementing advanced GenAI applications, including complex fine-tuning and LLM-based solutions
- Engaging in pre-sales technical discussions to understand client needs and provide guidance on Mistral's products and technologies
- Collaborating with researchers, AI engineers, and product teams on complex customer projects
- Contributing to open-source codebases for inference and fine-tuning
- Partnering with product and science teams to improve capabilities based on customer feedback
You'll bridge cutting-edge AI research with real-world enterprise applications, ensuring solutions are robust, scalable, and aligned with customer needs and Mistral's vision.
Required qualifications: 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products; proven experience implementing AI/ML products with APIs and front-end/back-end interfaces; expertise in fine-tuning LLMs, RAG, and agentic use cases; deep understanding of ML/LLM concepts and algorithms; strong Python coding skills; excellent communication abilities for both technical and non-technical audiences; fluent English.
Ideal candidates have contributed to open-source LLM projects, worked as Customer/Forward Deployed/Sales Engineers or Solutions Architects, and have deep learning experience with PyTorch.
